System and method for communicating media signals

ABSTRACT

A media streaming system for streaming media signals is provided. The media streaming system takes a library of separate and distinct CODECs that are provided as a searchable CODEC library and used in determining specific characteristics in the media signal to identify similar sections of the signal. The media streaming system uses a computer implemented intelligence system, such as an artificial intelligence mechanism to learn and capture the unique characteristics of a sinal as the signal is being streamed. The media streaming system also compresses and decompresses the media signal as the signals are streamed from a source media to a destination device.

RELATED APPLICATION

This application is a non-provisional application of “Reynolds et al. aprovisional application entitled “System and Method for CommunicatingMedia Signals”, application number 60/325,483, filed on Sep. 26, 2001.

FIELD OF THE INVENTION

This invention is a system and method for communicating media signalsbetween source and destination devices. More specifically, it is asystem and method for compressing and decompressing streaming and staticmedia signals for efficiently communicating those signals between sourceand destination devices using artificial intelligence mechanisms.

BACKGROUND OF THE INVENTION

The ability to efficiently communicate streaming and static mediabetween remotely located devices is a significant need that has emergedexponentially with the advent of networked communications such as theInternet. This need has been recently addressed with substantialdevelopment resources on a worldwide scale.

The term “media” is herein intended to mean information that may becommunicated in the form of a signal from a source device to adestination device for use by the destination device; and, where usedherein, media is generally contemplated to comprise either streaming orstatic media signals. For the purpose of this disclosure, the term “use”as applied to a destination device's operation on media signals isintended to include playing (e.g. sounds, images, video), processing(e.g. telemetry data), or any other use or operation that is theintended purpose of the media signal.

The terms “streaming media” are herein intended to mean media signalsthat comprise information intended to be communicated to and used by adestination device in a temporal, streaming fashion. The term“streaming” as applied to streaming media signals is herein intended toinclude signals communicated and processed in a continuous manner overtime, or signals that may be communicated in a series of discretepackets, pieces, or blocks that are interrelated and may be thereafterused by the destination device in a continuous, interrelated fashion.Examples of streaming media signals for the purpose of this disclosuretherefore include, without limitation, the following types of media:video, audio, audio combined with video, and data strings such astemporal telemetry. The terms “streaming media” are most typically usedby reference to digitized forms of data representing the subject media.

The terms “static media” are herein intended to generally mean mediathat is not “streaming” as defined above. Static media signals are ofthe type that generally may be communicated and are intended to be usedas a single packet, block, or piece. Static media therefore may includefor example, without limitation the following: a discrete image, anindividual and relatively temporally short video clip, a sound or soundbite, or a piece or block of information such as telemetry information.It is contemplated, however, that such a “single piece” of static mediamay be of sufficient magnitude to consist of a plurality of smallerpieces or sub-parts, such as for example regions or pixels of an overallimage, individual frames that together form a video clip, digital bitsthat together comprise a sound, a group of sounds that comprise a soundbite, or bits of information that together comprise a larger block ofinformation.

Streaming media generally includes data files that are significantlylarger than static media files, and also often represent many morevariables over the temporal communication of such files than experiencedwith most static media files. Therefore, the ability to efficientlycompress streaming media for appropriate communication to destinationdevices for use is often a much more complex and difficult to achievegoal. Accordingly, much of this disclosure is provided by referencespecifically to streaming media communication, and the present inventionhas been observed to provide significant benefits for suchcommunication. However, where streaming media is specifically referencedherein with respect to this background, and further with respect to themany benefits of the present invention herein disclosed, static media isalso further contemplated where appropriate according to one of ordinaryskill.

Many different “type-specific” media systems have been in use for quitea long time for transmitting specific types (e.g. video, audio, image,voice, etc.) of streaming and static media signals between sources andremote destinations. Typical examples of such type-specific mediasystems include television transmission systems, telephone line systems,and radio transmission systems, and every television, telephone, andradio is therefore a receiving device for media. Accordingly, the needsfor efficient communication of streaming and static media touch uponmany diverse communications industries, including for example thetelephone, television, movie, music, and more recently interactivegaming industries.

Moreover, many medial communications systems, including the variouslong-standing type-specific systems, are also “format specific”, whereinthe subject media signals are communicated in a particular format suchthat the source, transmission channel, and destination device must bespecifically compliant to work within that format. Examples of formatspecific media systems include for example encoded cable televisionsystems that work only for certain types of media and only delivered inparticular encoded formats from the cable carrier. Therefore, thesesystems, in hardware and software, are generally dedicated to only thetype and format of media to be provided by the content provider.

Society's needs have outpaced the abilities of these dedicated,content-specific and format-specific systems. In particular, thesededicated systems are not structured to accommodate the ever increasingclient demand, real-time, for specified streaming media. Still further,technology developments in the recently interconnected world has temptedthe palate of society for the ability to pull, receive, push, and sendmultiple types of media in multiple formats using one device. Moreover,content providers need to be able to deliver many different mediasignals to many different types of devices in their clients' offices,living rooms, and hands. Individuals and corporations also desire tocommunicate with each other using various different formats and usingvarious different respective devices.

Accordingly, a significant industry has emerged for delivering streamingand static media over the centralized network of the Internet. Contentdelivery companies are currently delivering a wide range of streamingmedia, from live horse racing and entertainment to medical telemetry andeducation, over the Internet, and in video and audio formats. Accordingto one published report from DFC Intelligence, video streaming on theInternet grew 215 percent in 2000 to over 900 million total streamsaccessed. This includes broadband streams, which made up almost 29percent of total accesses. This same report also estimates that as muchas 15 percent of available stream inventory is now being exploited within-stream advertising. In another report published by Internetresearcher Jupiter Media Metrix, business spending alone on streamingvideo technology will balloon from one-hundred forty million (US$140M)US dollars in 2000 to nearly three billion (US$3B) US dollars by 2005 ascompanies turn to electronic interaction in communicating withemployees, consumers and other businesses.

Still further, the population explosion and increasing number of peopletransmitting on these systems has severely impacted the availablebandwidth for available information. Therefore, the ability to streammedia efficiently, using limited bandwidth resources and limitedavailable transmission speeds, is of increased societal importance.

Compression/Decompression Algorithms (“CODECS”)

In view of the exponential demand for communicating the different typesof media, various compression/decompression systems (“CODEC(s)”) havebeen developed over many years, and have in particular become the recenttopic of significant research and development. Specific types of CODECSand systems for managing the operation of CODECS with respect tocommunicating streaming and static media signals have been developed forspecific types of media, including for example still-frame images suchas graphics and photographs, and streaming media.

Image CODECS

Various different types of static media CODECS have been developed, anda wide variety of these CODECS are widely known and used. One specifictype of static media that has been the topic of particular attentionincludes images (though a long series of interrelated image frames suchas in video context is generally treated as streaming media due to morecomplex variables, e.g. size and temporal relationship between frames,that significantly impact appropriate compression/decompression needs).Examples of static media CODECing is therefore herein exemplified byreference to certain specific types of conventional image CODECtechnologies and methods.

The two most common file formats for graphic images on the world wideweb are known as “GIF” and “JPEG” formats, generally considered therespective standards for drawings (e.g. line art) and photographs, andare further described together with other image compression modalitiesfor the purpose of further understanding as follows.

“JPEG” is an acronym for “Joint Photographic Experts Group”, and is agraphic image file that complies with ISO standard 10918. Commonly usedfor photograph compression/decompression, a JPEG file is created bychoosing from a range of compression qualities, or, as has also beendescribed, by choosing from one of a suite of compression algorithms. Inorder to create a JPEG file, or convert an image from another format toJPEG, the quality of image that is desired must be specified. Ingeneral, because the highest quality results in the largest file, atrade-off may then be made, as chosen by the user, between image qualityand image size. The JPEG mode of compression generally includes 29distinct coding processes although a JPEG implementer may not use themall. A JPEG image is typically given a name suffix “.jpg”.

“GIF” is an acronym for “Graphics Interchange Format”, and is generallyconsidered the de facto standard form of drawing imagecompression/decompression for Internet communication. GIF formattinguses a compression algorithm known as the LZW algorithm, which wasdeveloped by Abraham Lempel, Jacob Ziv, and Terry Welch and madecommercially available by Unisys Corporation (though in general suchalgorithm has been made publicly available without requiring fee-bearinglicenses). More specifically, a “LZW” compression algorithm takes eachinput sequence of bits of a given length (e.g. 12 bits) and creates anentry in a table, sometimes called a “dictionary” or “codebook”, forthat particular bit pattern. The entry consists of the pattern itselfand a shorter code. As input is read, any pattern that has been readbefore results in the substitution of the shorter code, effectivelycompressing the total amount of input to something smaller. Earlierapproaches, known as LZ77 and LZ78, did not include the look-up table aspart of the compressed file. However, the more recent LZW algorithmmodality does include the table in the file, and the decoding programthat decompresses the file for viewing is able to build the table itselfusing the algorithm as it processes the encoded input. The GIF formatuses the 2D raster data type (associated with display screens usingraster lines) and is encoded in binary.

Two versions of GIF formats include GIF 87a, and more recently GIF89athat allows for “animated GIF” file creation, or short sequences ofimages within a single GIF file that are played in sequence to presentmovement or change in the image (either in an endless loop or through aprogression that reaches an end). GIF89A also allows for, and also for“interlaced GIF”, which is a GIF image that arrives and is displayed bythe receiver first as a fuzzy outline of an image that is graduallyreplaced by seven successive waves of bit streams that fill in themissing lines until full resolution is reached. Interlaced GIF allows,for example, a viewer using 14.4 Kbps and 28.8 Kbps modems to observe abriefer wait-time before certain information in a subject image may beprocessed, such as for example to make decisions (e.g. to click on theimage to execute an operation such as a link).

By presenting waves of resolution filling image sequences, interlacedGIF is similar to “Progressive JPEG”, which describes an image createdusing the JPEG suite of compression algorithms that will “fade in” insuccessive waves. While the progressive JPEG is often observed to bemore appealing way to deliver an image at modem connection speeds, userswith faster connections may not likely notice a difference.

“PNG” or “Portable Network Graphics” format has been more recentlydeveloped for image compression and that, in time, has been publicizedto replace the GIF format for Internet use (though not generally theJPEG format allowing size/quality trade-offs). This format has beendeveloped for public consumption and development. Similar to GIF, PNG isconsidered a “lossless” compression format, and therefore all imageinformation is restored when a compressed file is decompressed duringviewing. However, PNG formatted files are generally intended to be from10 to 30 percent more compressed than with a GIF format. Further aspectsof PNG file formats are provided as follows: (i) color transparency maynot be limited to only one color, but the degree of transparency may becontrolled (“opacity”); (ii) “interlacing” of images is improved versusstandard GIF; (iii) “gamma correction” is enabled, allowing for “tuning”of images in terms of color brightness required by specific displaymanufacturers; (iv) images can be saved using true color, palette, andgray-scale formats similar to GIF; and (v) “animation” is generally notsupported, though PNG is generally considered extensible and thereforesoftware may be layered to provide for such scriptable image animation.

“TIFF” is an acronym for “Tag Image File Format”, and is a common formatfor exchanging raster graphics (or “bitmap”) images between applicationprograms, such as for example graphics used for scanner images. A TIFFfile is usually given a name suffix of “.tif” or “.tiff”, and hadgenerally been developed in the mid-1980's with the support of AdobeSoftware, Microsoft, and Hewlett-Packard. TIFF files can be in any ofseveral classes, including gray scale, color palette, or RGB full color,the descriptions and differences of which are further developedelsewhere herein this disclosure. TIFF files may also include files withJPEG, LZW, or CCITT Group 4 standard run-length image compression, whichare also further described elsewhere herein. As one of the most commongraphic image formats, TIFF files are typically used in desktoppublishing, faxing, 3-D applications, and medical imaging applications.

Video CODECS

Video compression has been the topic of intense development for variousapplications, including, for example: pre-recorded video (e.g.“video-on-demand”), teleconferencing, and live video (e.g. broadcasts).“Desk-top” computers, wireless devices, conventional televisions, andhigh definition televisions are examples of the different types ofreceiving devices that an efficient video compression system must serve.

In general, video CODEC algorithms operate on either or both of anindividual, frame-by-frame basis, and/or on a “temporal compression”basis wherein each frame is the most common video compression algorithmsin conventional use are based on several mathematic principles,including the following: Discrete Cosine Transforms (“DCT”), WaveletTransforms and Pure Fractals.

“Discrete Cosine Transforms” or “DCT's” are by far the most populartransforms used for image compression applications. In general, DCT is atechnique for representing waveform data as a weighted sum of cosines.The DCT is similar to the discrete Fourier transform: it transforms asignal or image from the spatial domain to the frequency domain. The DCThelps separate the image into parts (or spectral sub-bands) of differingimportance (with respect to the image's visual quality). Reasons for itspopularity include not only good performance in terms of energycompaction for typical images but also the availability of several fastalgorithms. DCTs are used in two international image/video compressionstandards, JPEG and MPEG.

“Wavelet transforms” are generally mathematical algorithms that convertsignal data into a set of mathematical expressions that can then bedecoded by a destination receiver device, such as for example in amanner similar to Fourier transform. Wavelets have been observed toenhance recovery of weak signals from noise, and therefore imagesprocessed in this manner can be enhanced without significant blurring ormuddling of details. For this reason, wavelet signal processing has beenparticularly applied to X-ray and magnetic-resonance images in medicalapplications. In Internet communications, wavelets have been used tocompress images to a greater extent than is generally possible withother conventional methods. In some cases, the wavelet-compressed imagecan be as small as about 25 percent the size of a similar quality imageusing the more familiar JPEG format, which is discussed in furtherdetail elsewhere in this disclosure. Thus, for example, a photographthat requires 200 Kb and takes a minute to download in JPEG format mayrequire only 50 Kb and take only 15 seconds to download inwavelet-compressed format. A wavelet-compressed image file is oftengiven a name suffix “.wif”, and either the receiver (e.g. Internetbrowser on a computer receiver) must support these format specificfiles, or a plug-in program will be required to read such file.

Fractal image compression is a modern technique of lossy image codingthat provides several improvements over existing Fourier seriescompression schemes. Edge depiction is improved since, when modeled as astep function, edges require a large number of Fourier series terms toproperly depict. Other advantages of fractals include fast decoding timeand scale independence. Fractal compression is based on Mandelbrot setswhich take advantage of a self similar, scaling dependent, statisticalfeature of nature (Mandelbrot, 1983). Fractal compression anddecompression involves a clustering approach to find regions which showthe same characteristics as a sample region independent of rotation andscale. The fractal image compresses images as recursive equations andinstructions about how to reproduce them. The equations describe theimage in terms of the relationships between its components. Thereduction in storage need is due to the fact that fractal compressionsaves equations and instructions instead of a pixel representation ofthe image.

“MPEG” is an acronym for Moving Picture Experts Group and has come to beused synonymously with certain evolving video and audio compressionstandards promulgated therefrom. In general, to use MPEG video files, apersonal computer is required with sufficient processor speed, internalmemory, and hard disk space to handle and play the typically large MPEGfile, usually given the name suffix “.mpg”. A specified MPEG viewer orclient software that plays MPEG files must be available on the clientsystem, and generally can be downloaded shareware or versions ofcommercial MPEG players from various sites on the Web. The modes ofoperation for MPEG formatted media are herein described by reference tothese sequentially evolved standards as follows.

More specifically, MPEG-1 standard was designed for coding progressivevideo generally at a transmission rate of about 1.5 Mbps. This wasgenerally designed for the specific application for Video-CD and CD-Imedia. MPEG-1 audio layer-3 (“MP3”) has also evolved from early MPEGwork. “MPEG-2” is a standard generally designed for coding interlacedimages at transmission rates above 4 Mbps, and was generally intendedfor use with digital TV broadcast and digital versatile disk. Though itis generally observed that many MPEG-2 players can handle MPEG-1 data aswell, the opposite is not generally observed to be true and MPEG-2encoded video is generally incompatible with MPEG-1 players. Yet anotherprogressive standard, “MPEG-3”, has also been proposed for use with highdefinition television (“HDTV”), though in general MPEG-3 has merged withMPEG-2 which is generally believed to meet the HDTV requirements.Finally, an “MPEG4” standard has also been most recently developed andis intended to provide a much more ambitious standard to address speechand video synthesis, fractal geometry, and computer visualization, andhas further been disclosed to incorporate artificial intelligence inorder to reconstruct images.

MPEG-1 and -2 standards define techniques for compressing digital videoby factors varying from 25:1 to 50:1. This compression is achievedaccording to these standards generally using five different compressiontechniques: (i) discrete cosine transform (DCT), which is afrequency-based transform; (ii) “quantization”, which is a technique forlosing selective information, e.g. lossy compression, that can beacceptably lost from visual information; (iii) “Huffman” coding, whichis a technique of lossless compression that uses code tables based onstatistics about the encoded data; (iv) “motion compensated predictivecoding”, wherein differences in what has changed between an image andits preceding image are calculated and only the differences are encoded;and (v) “bi-directional prediction”, wherein some images are predictedfrom the pictures immediately preceding and following the image.

Further more detailed examples of commercially available videocompression technologies include: Microsoft Media Player™ (availablefrom Microsoft Corporation), RealPlayer™ or RealSystem G2™ (commerciallyavailable from Real Networks™), Apple's QuickTime™ (commerciallyavailable from Sorenson™); and “VDO”. The Microsoft Media Player™ isgenerally believed to apply the MPEG standard of CODEC forcompression/decompression, whereas the others have been alleged to useproprietary types of CODECS. Standard compression algorithms, such asMPEG4, have made their way into the hands of developers who are buildingembedded systems for enterprise streaming, security, and the like.

One example of a more recent effort to provide streaming video solutionsover Wireless and IP networks has been publicized by a company namedEmblaze Systems (LSE:BLZ). This company has disclosed certain technologythat is intended for encoding and playback of live and on-demand videomessages and content on any platform: PC's, PDA's, Video cell phones andInteractive TV. Emblaze Systems is believed to be formerly GEOInteractive Media Group. The following Published International PatentApplications disclose certain streaming media compression technologiesthat is believed to be related to Emblaze Systems to the extent that GEOInteractive Media Group is named as “Assignee”: WO9731445 to Carmel etal.; and WO9910836 to Carmel. The disclosures of these references areherein incorporated in their entirety by reference thereto.

Another company that has published CODEC technology that is intended toimprove communication of streaming media for wireless applications isPacketvideo™ Corporation, more specifically intending to communicatestreaming video to cellular phones. In addition, they are believed to bepromoting CODEC technology that is intended to track temporalscalability and signal error resistance in order to protect video andaudio streams from the hazards of the wireless environment. U.S. Pat.No. 6,167,092 to Lengwehasatit discloses further examples of certainstreaming media compression/decompression technology that are believedto be associated with Packetvideo as the named “Assignee” on the face ofthis Patent reference. The disclosure of this patent reference is hereinincorporated in its entirety by reference thereto.

Another prior reference discloses CODEC technology that is intended toprovide a cost effective, continuously adaptive digital video system andmethod for compressing color video data for moving images. The methodinvolves capturing an analog video frame and digitizing the image into apreferred source input format for compression using a combination ofunique lossy and lossless digital compression techniques includingsub-band coding, wavelet transforms, motion detection, run length codingand variable length coding. The system includes encoder and decoder(CODEC) sections, generally disclosed to use a “Huffman” encoder, forcompression and decompression of visual images to provide highcompression that is intended to provide good to excellent video quality.The compressed video data provides a base video layer and additionallayers of video data that are multiplexed with compressed digital audioto provide a data stream that can be packetized for distribution overinter or intranets, including wireless networks over local or wideareas. The CODEC system disclosed is intended to continuously adjust thecompression of the digital images frame by frame in response tocomparing the available bandwidth on the data channel to the availablebandwidth on the channel for the previous frame to provide an outputdata stream commensurate with the available bandwidth of the networktransmission channel and with the receiver resource capabilities of theclient users. The compression may be further adjusted by adjustment ofthe frame rate of the output data stream.

Further more detailed examples of CODEC systems that are intended foruse at least in part for streaming video communication are disclosed inthe following U.S. Pat. No. 6,081,295 to Adolph et al.; U.S. Pat. No.6,091,777 to Guetz et al.; U.S. Pat. No. 6,130,911 to Lei; U.S. Pat. No.6,173,069 B1 to Daly et al.; U.S. Pat. No. 6,263,020 B1 to Gardos etal.; U.S. Pat. No. 6,272,177 to Murakami et al.; and U.S. Pat. No.6,272,180 B1 to Lei. The disclosures of these references are hereinincorporated in their entirety by reference thereto.

Most if not all prior streaming video compression methodologies look tothe extremely complex mathematical tools within such CODECS, and subtlechanges to them, to carry “one size fits all” video over public andprivate networks of all types, from ultra-low bandwidth networks such asthat found in wireless networks, to satellite communications toultra-high speed fiber optic installations. Among the variousconventional methods of compression, there are generally user-definableparameters, including tradeoffs between image size, frame rate, colordepth, contrast, brightness, perceived frame quality, buffer length,etc. Further, within the algorithms themselves there are numerousnon-user definable qualities and weighted calculations. It is up to thedevelopers to set these one time for one “general” interest, and thenpackage and ship the product.

However, while the video streaming market continues to grow rapidly, theworld has not chosen one standard for compression as no one algorithm isideal for all video sources, destinations, or transmission modalities.While a first CODEC may be best for one type of signal, or for a firstportion of a signal (e.g. frame or scene comprising a series of frames),another second CODEC may be best for another type of signal, or evenanother second portion of the same signal. Still further, one CODEC maybe best suited for compression/decompression of a particular streamingsignal among send, receive, and transmission devices in a communicationsnetwork; another second CODEC may be better suited than the first forthe same streaming media signal but for another set of communicationdevice parameters. For example, some video streams may deliver color tohandheld devices while other video streams can take advantage of theloss of pixels in a black and white transmission to a cellular phone toincrease frame rate. Required sound quality, frame rates, clarity, andbuffering tolerance all decidedly impact the compression algorithm ofchoice for optimized video and audio delivery across multiple platforms.

In fact, certain communication device parameters may be sufficientlytransient during the streaming media transmission such that an initiallyappropriate CODEC for an initial set of parameters may be rendered lessefficient than another CODEC due to changes in those parameters duringthe same streamed signal transmission. Examples of such transientparameters include, without limitation: available band width in the datatransmission channel, available memory or processing power in either thesend or receiving devices, and dedicated display resolution/window inthe receiving device (e.g. minimizing windows on a screen). Theseproblems are compounded exponentially by a vast number of iterations ofdifferent combinations of such factors that may differentiate one CODECfrom another as being most efficient for compression, decompression, anddelivery of a specific streaming media signal along a particularcommunications device system.

As CODEC systems are “format-specific”, source and destination devicesmust be “pre-configured” to communicate media signals between each otheraccording to common, specific compression/decompression modalities, elsetranscoders must be used. However, even if conventional transcoders areused, constraints in the communication system (e.g. source, transmissionchannel, destination device) are not generally considered and thecommunication may be significantly faulty. For the purpose of furtherillustration, FIGS. 1A and 1B show two different schematicrepresentations of conventional methods for communicating media betweensource 110-120 and destination devices 130-140. These illustrationsspecifically exemplify streaming video communication, though other mediaforms may be represented by similar systems.

It has been observed that CODEC algorithms can generally be modified fora specific application and then perform better than a similar unmodifiedset over that limited example. However, this generally must be doneeither for a series of frames, or ideally, for each individual frame.Some DCT based algorithms have as many as two billion mathematicaloperations occurring for each frame at higher resolutions and lowerperceived quality. This is entirely too much math for average machines,even commercial servers, to perform thirty to sixty times in a singlesecond. This is the reason for the advent of the dedicated compressionboard or ASIC.

Audio CODECS

In addition to society's recent interests in improving videocompression, audio compression has likewise been the topic ofsignificant efforts also for various live or pre-recorded applications,including audio broadcast, music, transmission synchronized with video,live interactive voice (e.g. telephone). Any and all of these audiocompression applications must be compatible with a wide range ofclient-side receiver/players, such as on a multitude of handheld ordesk-top devices having widely varied capabilities and operatingparameters.

Conventional audio CODECS generally comprise several different types, afew of which are herein briefly summarized for the purpose ofillustration.

“Code Excited Linear Prediction” or “CELP” is a type of speechcompression method using waveform CODECS that use“Analysis-by-Synthesis” or “AbS” within the excitation-filter frameworkfor waveform matching of a target signal. CELP-based CODECS haverecently evolved as the prevailing technique for high quality speechcompression, and has been published to transmit compressed speech oftoll-quality at data rates nearing as low as about 6 kbps. However, atleast one publication discloses that the quality of CELP coded speech isreduced significantly for bit rates at or below 4 kbps.

“Vocoders” are speech CODECS that are not based on the waveform codingscheme, but rather use a quantized parametric description of the targetinput speech to synthesize the reconstructed output speech. Vocodershave been disclosed to deliver better speech quality at low bit-rates,such as about 4 kbps, and have been developed for such applications. Lowbit rate vocoders use the periodic characteristics of voiced speech andthe “noise-like” characteristics of stationary unvoiced speech forspeech analysis, coding and synthesis. Some early versions of vocoders(e.g. federal standard 1015 LPC-10, use a time-domain analysis andsynthesis method. However, most of the more recent versions, which atleast one publication labels “harmonic coders”, utilize a harmonicspectral model for voiced speech segments.

Notwithstanding the previous description of certain specific speechcompression techniques, a vast number of speech CODECs and standardshave been developed by industry and managed by industry and nonprofitgroups. Examples of such groups include without limitation thefollowing, and their standards are often used as reference types ofCODECS: the European Telecommunications Standards Institute (“ETSI”);the Institute of Electrical and Electronics Engineers (“IEEE”); and theInternational Telecommunication Union Telecommunications StandardsSector (“ITU-T”), formerly the “CCWI”.

One more recently disclosed method and apparatus for hybrid coding ofspeech, specified at 4 Kbps, encodes speech for communication to adecoder for reproduction of the speech where the speech signal isclassified into three types: (i) steady state voiced or “harmonic”; (ii)stationary unvoiced; and (iii) “transitory” or “transition” speech. Aparticular type of coding scheme is used for each class. Harmonic codingis used for steady state voiced speech, “noise-like” coding is used forstationary unvoiced speech, and a special coding mode is used fortransition speech, designed to capture the location, the structure, andthe strength of the local time events that characterize the transitionportions of the speech. The compression schemes are intended to beapplied to the speech signal or to the LP residual signal.

Another recently disclosed method and arrangement for adding a newspeech encoding method to an existing telecommunication system is alsosummarized as follows. A CODEC is introduced into a speech transmittingtransceiver of a digital telecommunications system in order to use a“new” CODEC and an “old” CODEC in parallel in the system. A CODEC isselected by implementing a handshaking procedure between transceiverswhere a speech encoding method is implemented in all transceivers andpreviously used in the telecommunications system concerned. Thehandshaking is used at the beginning of each connection. At thebeginning of a phone call and after handover, the method checks whetherboth parties can also use the new speech encoding. The handshakingmessages have been selected so that their effect on the quality ofspeech is minimal, and yet so that the probability of identifying themessages is maximal.

Still another relatively recent reference discloses a tunable perceptualweighting filter for tandem CODECS intended for use in speechcompression. Specific filter parameters are tuned to provide improvedperfromance in tandeming contexts. More specifically, the parametersused are 10^(th) order LPC predictor coefficients. This system isspecified to use “Low-Delay Excited Linear Predictive” CODECS, or“LD-CELP”.

Further more detailed examples of streaming audio communications systemsusing CODECS such as according to the examples just described areprovided in the following US Patent references: U.S. Pat. No. 6,144,935to Chen et al.; U.S. Pat. No. 6,161,085 to Haavisto et al.; and U.S.Pat. No. 6,233,550 to Gersho. The disclosures of these references areherein incorporated in their entirety by reference thereto.

Artificial Intelligence (“AI”) and Neural Networks with CODECS

Various systems and methods have been recently disclosed that areintended to integrate artificial intelligence (“AI”) or neural networkswith the compression and decompression of streaming media signals.

The terms “artificial intelligence” are herein intended to mean thesimulation of human intelligence processes by computer systems,including learning (the acquisition of information and rules for usingthe information), reasoning (using the rules to reach approximate ordefinite conclusions), and self-correction. Particular applications ofAI include “expert systems”, which are computer programs that simulatejudgment and behavior of a human or organization that has expertknowledge and experience in a particular field. Typically, expertsystems contain a knowledge base to each particular situation that isdescribed to the program, and can be enhanced with additions to theknowledge base or to the set of rules.

The terms “neural network” are herein intended to mean a system ofprograms and data structures that approximates the operation of thehuman brain, usually involving a large number of processors operating inparallel, each with its own small sphere of knowledge and access to datain its local memory. Typically, a neural network is initially trained orfed large amounts of data and rules about data relationships, afterwhich a program can tell the network how to behave in response to anexternal stimulus (e.g. input information). In making determinations,neural networks use several principles, including without limitationgradient-based training and fuzzy logic. Neural networks may be furtherdescribed in terms of knowledge layers, generally with more complexnetworks having deeper layers. In “feedforward” neural network systems,learned relationships about data can “feed forward” to higher layers ofknowledge. Neural networks can also learn temporal concepts and havebeen widely used in signal processing and time series analysis. Otherpublished applications of neural networks include oil exploration dataanalysis, weather prediction, the interpretation of nucleotide sequencesin biology labs, and the exploration of models of thinking andconsciousness.

The terms “fuzzy logic” are herein intended to mean an approach tocomputing based upon “degrees of truth” rather than “Boolean logic”which operates within only a true/false (or “binary”, as 1 or 0) domain.Fuzzy logic was first advanced by Dr. Lotfi Zadeh of the University ofCalifornia at Berkeley in the 1960's in relation to work on a problem ofcomputer understanding of natural language, which is not easilytranslated into absolute Boolean logic terms. Fuzzy logic often doesinclude the cases of 0 and 1 as extreme cases of truth, but alsoincludes the various states of truth in between (e.g. a determination ofthat the state of being is at some threshold, such as 0.98, may assistsin making a decision to assign a 1 with an acceptably low occurrence oferror in an operation).

One example of a previously disclosed streaming mediacompression/decompression system intended to use with artificialintelligence through a neural network uses a Radon transform in order tocompress data such as video data. Several previously disclosed AI and/orneural network systems are intended to use AI and/or neural networks forthe purpose of error correction during use of certain specified losslesscompression CODECS. For example, a learning system is employed todetermine a difference between what was received by a receiver aftercompression and transmission and what is predicted to have been receivedat the transmission end. That difference is processed as learning tomodify the tuning of the CODEC for an additional transmission.

Another example of a disclosed method and device is intended toextrapolate past signal-history data for insertion into missing datasegments in order to conceal digital speech frame errors. Theextrapolation method uses past-signal history that is stored in abuffer. The method is implemented with a device that is disclosed toutilize a finite-impulse response (“FIR”), multi-layer, feed-forward,artificial neural network that is trained by back-propagation forone-step extrapolation of speech compression algorithm (“SCA”)parameters. Once a speech connection has been established, the speechcompression algorithm device begins sending encoded speech frames. Asthe speech frames are received, they are decoded and converted back intospeech signal voltages. During the normal decoding process,pre-processing of the required SCA parameters will occur and the resultsstored in the past-history buffer. If a speech frame is detected to belost or in error, then extrapolation modules are executed andreplacement SCA parameters are generated and sent as the parametersrequired by the SCA. In this way, the information transfer to the SCA isintended to be transparent, and the SCA processing continues as usual.This disclosure alleges that the listener will not normally notice thata speech frame has been lost because of the smooth transition betweenthe last-received, lost, and next-received speech frames.

Further more detailed examples of systems that are intended to useartificial intelligence and/or neural networks in systems for mediacompression and/or decompression, generally relating to mediatype-specific CODEC methods (e.g. speech, video), are variouslydisclosed in the following US Patent References: U.S. Pat. No. 5,005,206to Naillon et al.; U.S. Pat. No. 5,041,916 to Yoshida et al.; U.S. Pat.No. 5,184,218 to Gerdes; U.S. Pat. No. 5,369,503 to Burel et al.; U.S.Pat. No. 5,598,354 to Fang et al.; U.S. Pat. No. 5,692,098 to Kurdziel;U.S. Pat. No. 5,812,700 to Fang et al.; U.S. Pat. No. 5,872,864 to Imadeet al.; U.S. Pat. No. 5,907,822 to Prieto, Jr.; and U.S. Pat. No.6,216,267 to Mitchell. Still further examples are provided in thefollowing Published International Patent Applications: WO 01/54285 toRising; EPO 0372608 A1 to Naillon et al. The disclosures of all thesereferences cited in this paragraph are herein incorporated in theirentirety by reference thereto.

Other disclosures of CODEC systems using feedback or other systems foroperating CODECS for use in processing a variety of streaming mediasignals, but that are not believed to specifically use the labels “AI”or “neural networks”, are disclosed in the following U.S. Pat. No.6,072,825 to Betts et al.; U.S. Pat. No. 6,182,034 B1 to Malvar; U.S.Pat. No. 6,253,165 B1 to Malvar; U.S. Pat. No. 6,256,608 B1 to Malvar.The disclosures of these references are herein incorporated in theirentirety by reference thereto.

Notwithstanding the significant advancements in CODEC algorithmsthemselves, and despite prior intended uses of AI and other feedbacksystems for operating CODECS in order to improve compressionefficiencies in communication, there is still a need for significantimprovement in the ability to efficiently provide a wide variety ofstreaming media signals to a wide variety of destination receiverdevices over a wide variety of transmission channels with variedbandwidths and communication protocols.

There is still a need to incorporate AI and/or neural networks to applyan appropriate CODEC for communication of a streaming media signal basedupon a variety of parameters, including without limitation one or moreof the following: (a) the automated choosing of an appropriatelyoptimized CODEC from a library of available CODECS of different typesand operation, including in particular based upon an intelligentknowledge of the chosen CODEC's operation compared to the other CODEC'soperation and/or against a standard, (b) a pre-trained and/oriteratively learned knowledge of the particular CODEC's operation withina given set of operating parameters representative of the existingsituation; and (c) a tuning of the appropriate CODEC based upon anintelligent knowledge of its operation with respect to either or both ofthe existing situation or a test situation with reference parameters.

In particular, there is still a need for such an intelligent CODECsystem that bases an applied CODEC upon an existing situation that isdefined by one or more of the following: parameters of the streamingmedia signal itself; parameters of the transmission channel capabilitiesand constraints; and parameters of the receiver device capabilities andconstraints.

Still further, there is also still a need for such an intelligent CODECsystem that operates based upon an intelligent knowledge with respect toall of these operations and situational parameters in order to optimizethe appropriate compression, transmission, decompression, and playing ofthe subject streaming media signal.

Conventional Transcoders for Streaming Media

Also of recent interest in the field of streaming media communication isproviding intercommunication between the wide array of “format-specific”encoding systems in present use. An existing field of various differentformat-specific systems and pre-encoded content has created a widelyfragmented ability to process encoded content, resulting in asignificant quagmire of compatibility issues between content providersand client users. If one client desires to see or hear streaming contentfrom a particular source and that content must be put through a CODECfor compression, a compatible LO CODEC must be used on the client sidefor decompression to enjoy the signal. Unfortunately, source content isoften married to only a few, and often only one, specific CODEC schemes.Therefore, if a client requests such encoded content (or if the sourcedesires to push the encoded content to a particular client), one of twocriteria must be met: (1) the client must download or otherwise possessthe format-specified CODEC (decoder); or (2) the source media must beput through a “transcoder” in order to decode the source media from thefirst format into a second format that is compatible with the client'sdevice/system. The term “transcoder” is herein intended to mean a systemthat converts a media signal from one encoded (i.e. compressed) formatto another.

Various techniques for transcoding one media format into another havebeen previously disclosed. FIG. 1C shows one illustrative example of thegeneral process that is characteristic of many known transcodingtechniques. More specifically, a request 159 is first received from aparticular type of device or player for content that exists in aninitial, uncompatible format. According to the specific example shown inFIG. 1C, a request 159 from a Microsoft Media™ Player for Real™ VideoContent is received. As the content is specifically requested, thecontent is decoded from the initial format (e.g. Real-encoded format),and is then “re-encoded” into the appropriate format for the requestingplayer (e.g. Microsoft Media™ format). This re-encoded media is thenserved to the requesting client for decoding within the resident systemof that player.

This conventional system has significant scalability limitations, inthat simultaneous feeds on multiple channels for multiple clients mustbe supported by an equal number of transcoders. For example, FIG. 1Dshows a schematic implementation of the conventional transcodingtechnique just described as it manages four simultaneous stream requestsfrom four Microsoft Media Players, wherein the requested content isinitially encoded in Real™ format. The system architecture necessary tosupport the four encoders 151-154 and four decoders 155-158 requiressignificant computing resources. For example, it is believed that eachencoder 151-154 provided in the example requires a computer having a 600MHz (e.g. Pentium™ III) having 128 Mbytes of RAM available, or dual 400MHz processors (e.g. Pentium II) with 256 Mb available RAM. It isfurther believed that each decoder 155-158 needs a 233 MHz machine (e.g.Pentium™ II) having 64 Mb of available RAM. So, four such streamsrequires the equivalent of a Quad 900 Xeon (available from Compaq,Hewlett Packard, Dell and IBM, estimated to cost at the time of thisdisclosure about $9K retail). This is for four simultaneousstreams—society is presently demanding thousands upon thousands ofsimultaneous streams.

There is still a need for a transcoder system that efficiently convertsmultiple format-specifically encoded streaming media signals intomultiple other formats using minimal computing resources and in acost-efficient manner.

Parameters Affecting Media Communication

For the purpose of further illustrating the many variables that mayimpact the choice of an appropriate CODEC in order to communicate aparticular streaming media signal to a desired target, the following isa brief summary of various different types of streaming video formatsand processing systems. It is believed that these different systems eachgenerally require different types of compression modalities (e.g.CODECS) in order to optimize communication and playing of streamingmedia signals in view of available transmission speeds and bandwidth, aswell as receiver processing parameters.

Although certain specific types of communications formats and systemsare further herein described in detail, the following Table 1 provides asummary of a significant cross-section of the various differentcommunications systems and transmission carriers currently available ordisclosed in view of available speed or bandwidth.

TABLE 1 Data Rates of Various Communications Carrier systems TechnologySpeed Physical Medium Application GSM mobile telephone 9.6 to 14.4 KbpsRF in space (wireless) Mobile telephone for business and personalservice use High-Speed Circuit-Switched Up to 56 Kbps RF in space(wireless) Mobile telephone for business and personal Data service(HSCSD) use Regular telephone service Up to 53 Kbps Twisted pair Homeand small business access (POTS) Dedicated 56 Kbps on Frame 56 KbpsVarious Business e-mail with fairly large file Relay attachments DS0 64Kbps All The base signal on a channel in the set of Digital Signallevels General Packet Radio System 56 to 114 Kpbs RF in space (wireless)Mobile telephone for business and personal (GPRS) use ISDN BRI: 64 Kbpsto 128 Kbps BRI: Twisted-pair BRI: Faster home and small business accessPRI: 23 (T-1) or 30 (E1) assignable 64- PRI: T-1 or E1 line PRI: Mediumand large enterprise access Kbps channels plus control channel; up to1.544 Mbps (T-1) or 2.048 (E1) IDSL 128 Kbps Twisted-pair Faster homeand small business access Apple Talk 230.4 Kbps Twisted pair Local areanetwork for Apple devices; several networks can be bridged; non-Appledevices can also be connected Enhanced Data GSM 384 Kbps RF in space(wireless) Mobile telephone for business and personal Ennvironment(EDGE) use Satellite 400 Kbps (DirecPC and others) RF in space(wireless) Faster home and small enteprise access Frame relay 56 Kbps to1.544 Mbps Twisted-pair or coaxial cable Large company backbone for LANsto ISP ISP to Internet infrastructure DS1/T-1 1.544 Mbps Twisted-pair,coaxial cable, or Large company to ISP optical fiber ISP to Internetinfrastructure Universal Mobile Up to 2 Mbps RF in space (wireless)Mobile telephone for business and personal Telecommunications Serviceuse (available in 2002 or later) (UMTS) E-carrier 2.048 Mbps Twistedpair, coaxial cable, or 32-channel European equivalent of T-1 opticalfiber T-1C (DS1C) 3.152 Mbps Twisted pair, coaxial cable, or Largecompany to ISP optical fiber ISP to Internet infrastructure IBM TokenRing/802.5 4 Mbps (also 16 Mbps) Twisted pair, coaxial cable, or Secondmost commonly-used local area optical fiber network after EthernetDS2/T-2 6.312 Mbps Twisted pair, coaxial cable, or Large company to ISPoptical fiber ISP to Internet infrastructure Digital Subscriber Line 512Kbps to 8 Mbps Twisted pair (used as a digital, Home, small business,and enterprise (DSL) broadband medium) access using existing copperlines E-2 8.448 Mbs Twisted pair, coaxial cable, or Carries fourmultiplexed E-1 signals optical fiber Cable modem 512 Kbps to 52 MbpsCoaxial cable (usually uses Home, business, school access (see “Key andexplanation” below) Ethernet); in some systems, telephone used forupstream requests Ethernet 10 Mbps 10BASE-T (twisted-pair); Most popularbusiness local area network 10BASE-2 or -5 (coaxial cable); (LAN)10BASE-F (optical fiber) IBM Token Ring/802.5 16 Mbps (also 4 Mbps)Twisted pair, coaxial cable, or Second most commonly-used local areaoptical fiber network after Ethernet E-3 34.368 Mbps Twisted pair oroptical fiber Carries 16 E-1 signals DS3/T-3 44.736 Mbps Coaxial cableISP to Internet infrastructure Smaller links within Internetinfrastructure OC-1 51.84 Mbps Optical fiber ISP to Internetinfrastructure Smaller links within Internet infrastructure High-SpeedSerial Interface Up to 53 Mbps HSSI cable Between router hardware andWAN lines (HSSI) Short-range (50 feet) interconnection between slowerLAN devices and faster WAN lines Fast Ethernet 100 Mbps 100BASE-T(twisted pair); Workstations with 10 Mbps Ethernet cards 100BASE-T(twisted pair); can plug into a Fast Ethernet LAN 100BASE-T(opticalfiber) Fiber Distributed-Data 100 Mbps Optical fiber Large, wide rangeLAN usually in a large Interface (FDDI) company or a larger ISP T-3D(DS3D) 135 Mbps Optical fiber ISP to Internet infrastructure Smallerlinks within Internet infrastructure E-4 139.264 Mbps Optical fiberCarries 4 E3 channels Up to 1,920 simultaneous voice conversationsOC-3/SDH 155.52 Mbps Optical fiber Large company backbone Internetbackbone E-5 565.148 Mbps Optical fiber Carries 4 E4 channels Up to7,680 simultaneous voice conversations OC-12/STM-4 622.08 Mbps Opticalfiber Internet backbone Gigabit Ethernet 1 Gbps Optical fiber (and“copper” Workstations/networks with 10/100 Mbps up to 100 metersEthernet plug into Gigabit Ethernet switches OC-24 1.244 Gbps Opticalfiber Internet backbone SciNet 2.325 Gbps (15 OC-3 lines) Optical fiberPart of the vBNS backbone OC-48/STM-16 2.488 Gbps Optical fiber Internetbackbone OC-192/STM-64 10 Gbps Optical fiber Backbone OC-256 13.271 GbpsOptical fiber Backbone Comments & Key for Table: (i)The term “Kbps” asthe abbreviation for “thousands of bits per second.” In internationalEnglish outside the U.S., the equivalent usage is “kbits s⁻¹” or“kbits/s”. (ii) Engineers use data rate rather than speed, but speed (asin “Why isn't my Web page getting here faster?”) seems more meaningfulfor the less technically inclined. (iii) Relative to data transmission,a related term, bandwidth or “capacity,” means how wide the pipe is andhow quickly the bits can be sent down the channels in the pipe. These“speeds” are aggregate speeds. That is, the data on the multiple signalchannels within the carrier is usually allocated by channel fordifferent uses or among different users. Key: (i) “T” = T-carrier systemin U.S., Canada, and Japan . . . (ii) “DS” = digital signal (thattravels on the T-carrier or E-carrier) . . . (iii) “E” = Equivalent of“T” that uses all 8 bits per channel; used in countries other than U.S.Canada, and Japan . . . (iv) “OC” = optical carrier (Synchronous OpticalNetwork) “STM” = Synchronous Transport Modules (see SynchronousDigitalHeirarchy). (v) Only the most common technologies are shown. (vi)“Physical medium” is stated generally and doesn't specify the classes ornumbers of pairs of twisted pair or whether optical fiber is single-modeor multimode. (vii) The effective distance of a technology is not shown.(viii) There are published standards for many of these technologies.Cable modem note: The upper limit of 52 Mbps on a cable is to an ISP,not currently to an individual PC. Most of today's PCs are limited to aninternal design that can accommodate no more than 10 Mbps (although thePCI bus itself carries data at a faster speed). The 52 Mbps cablechannel is subdivided among individual users. Obviously, the faster thechannel, the fewer channels an ISP will require and the lower the costto support an individual user.

Internet Carrier Systems

Communication of streaming video via the Internet may take place over avariety of transmission modalities, including for example digitalsubscriber lines (“DSL”), “T1” lines, cable modem, plain old telephoneservice (“POTS”) dial-up modem, and wireless carriers. While adescription of the many different wireless transmission modalities istreated separately herein, a summary of various of these othertransmission modes is herein provided immediately below for the purposeof further illustration as follows.

The terms “POTS” or “plain old telephone service”, or “dial-up”, asapplied to communications transmission channels, are hereininterchangeably used. These terms are intended to mean “narrow-band”communication that generally connects end users in homes or smallbusinesses to a telephone company office over copper wires that arewound around each other, or “twisted pair”. Traditional phone servicewas created to let you exchange voice information with other phone usersvia an analog signal that represents an acoustic analog signal convertedinto an electrical equivalent in terms of volume (signal amplitude) andpitch (frequency of wave change). Since the telephone company'ssignaling is already set up for this analog wave transmission, it'seasier for it to use that as the way to get information back and forthbetween your telephone and the telephone company. Therefore, dial-upmodems are used to demodulate the analog signal and turn its values intothe string of 0 and 1 values that is called digital information. Becauseanalog transmission only uses a small portion of the available amount ofinformation that could be transmitted over copper wires, the maximumamount of data that you can receive using ordinary modems is about 56Kbps. The ability of your computer to receive information is constrainedby the fact that the telephone company filters information that arrivesas digital data, puts it into analog form for your telephone line, andrequires your modem to change it back into digital. In other words, theanalog transmission between your home or business and the phone companyis a bandwidth bottleneck.

With “ISDN”, or “Internet subscriber digital network”, which someconsider to be a limited precursor to DSL, incoming data rates up toabout 128 Kbps may be achieved for some end user clients.

A “DSL” or “digital subscriber line” is generally defined as a“broadband” transmission carrier for communicating high-bandwidthcommunication over ordinary copper telephone lines. Many different typesof DSL services have been disclosed, having generally varied data ratesand intended applications. Though further discussion is herein providedabout certain of these DSL types, the following Table 2 provides asummary of information for certain of these DSL types for the purpose offurther developing an overview understanding:

TABLE 2 Types of known DSL services. Data Rate Downstream; DSL TypeDescription Upstream Distance Limit Application IDSL ISDN DigitalSubscriber 128 Kbps 18,000 feet on 24 Similar to the ISDN BRI servicebut Line gauge wire data only (no voice on the same line) CDSL ConsumerDSL 1 Mbps downstream; less upstream 18,000 feet on 24 Splitterless homeand small business from Rockwell gauge wire service; similar to DSL LiteDSL Lite “Splitterless” DSL From 1.544 Mbps to 6 Mbps 18,000 feet on 24The standard ADSL; sacrifices speed (same as without the “truck roll”downstream, depending on the gauge wire for not having to install asplitter at G.Lite) subscribed service the user's home or businessG.Lite (same “Splitterless” DSL From 1.544 Mbps to 6 Mbps, 18,000 feeton 24 The standard ADSL; sacrifices speed as DSL Lite) withont the“truck roll” depending on the subscribed service gauge wire for nothaving to install a splitter at the user's home or business HDSL Highbit-rate Digital 1.544 Mbps duplex on two twisted-pair 12,000 feet on 24T1/E1 service between server and Subscriber lines; gauge wire phonecompany or Line 2.048 Mbps duplex on three twisted- within a company;pair lines WAN, LAN, server access SDSL Symmetric DSL 1.544 Mbps duplex(U.S. and Canada); 12,000 feet on 24 Same as for HDSL but requiring2.048 Mbps (Europe) on a single gauge wire only one line of twisted-pairduplex line downstream and upstream ADSL Asymmetric Digital 1.544 to 6.1Mbps downstream; 1.544 Mbps at Used for Internet and Web access,Subscriber Line 16 to 640 Kbps upstream 18,000 feet; motion video, videoon demand, 2.048 Mbps at remote LAN access 16,000 feet; 6.312 Mpbs at12,000 feet; 8.448 Mbps at 9,000 feet RADSL Rate-Adaptive DSL fromAdapted to the line, 640 Kbps to 2.2 Not provided Similar to ADSLWestell Mbps downstream; 272 Kbps to 1.088 Mbps upstream UDSLUnidirectional DSL Not known Not known Similar to HDSL proposed by acompany in Europe VDSL Very high Digital 12.9 to 52.8 Mbps downstream;4,500 feet at 12.96 ATM networks; Subscriber Line 1.5 to 2.3 Mbpsupstream; Mbps; Fiber to the Neighborhood 1.6 Mbps to 2.3 Mbpsdownstream 3,000 feet at 25.82 Mbps; 1,000 feet at 51.84 Mbps

Typically published data rates for DSL service, which may vary dependingupon distance from the central office of the offering service company,includes rates up to 6.1 Mbps (theoretically published at 8.448 Mbps),which is believed to enable continuous transmission of motion video,audio, and 3-D effects. More typical individual connections provide from512 Kbps to 1.544 Mbps downstream and about 128 Kbps upstream. A DSLline can carry both data and voice signals and the data part of the lineis continuously connected. DSL has been anticipated in some publicationsto replace ISDN in many areas and to compete with cable modem formultimedia communication to homes and businesses. DSL operates purelywithin the digital domain and does not require change into analog formand back. Digital data is transmnitted to destination computers directlyas digital data and this allows the phone company to use a much widerbandwidth for forward transmission. Meanwhile, if a client user chooses,the signal can be separated so that some of the bandwidth is used totransmit an analog signal so that a telephone and computer may be usedon the same line and at the same time.

Most DSL technologies require that a signal splitter be installed at ahome or business, requiring the expense of a phone company visit andinstallation. However, it is possible to manage the splitting remotelyfrom the central office. This is known as splitterless DSL, “DSL Lite,”G.Lite, or Universal ADSL (further defined below) and has recently beenmade a standard. Several modulation technologies are used by variouskinds of DSL, although these are being standardized by the InternationalTelecommunication Union (ITU). Different DSL modem makers are usingeither Discrete Multitone Technology (DMT) or Carrierless AmplitudeModulation (CAP). A third technology, known as Multiple Virtual Line(MVL), is another possibility.

A variety of parameters of DSL operation are variable and affect theeffective data rates that can be achieved. DSL modems generally followthe data rate multiples established by North American and Europeanstandards. In general, the maximum range for DSL without a repeater is5.5 km (18,000 feet). As distance decreases toward the telephone companyoffice, the data rate increases. Another factor is the gauge of thecopper wire. The heavier 24 gauge wire carries the same data ratefarther than 26 gauge wire. For destination devices beyond the 5.5kilometer range, DSL may still be provided, though only generally if therespective phone company provider has extended the local loop withoptical fiber cable.

To interconnect multiple DSL users to a high-speed network as a“backbone”, the telephone company uses a Digital Subscriber Line AccessMultiplexer (“DSLAM”). Typically, the DSLAM connects to an asynchronoustransfer mode (“ATM”) network that can aggregate data transmission atgigabit data rates. At the other end of each transmission, a DSLAMdemultiplexes the signals and forwards them to appropriate individualDSL connections.

“ADSL” or “Asymmetric Digital Subscriber Line” is the form of DSL thatwill become most familiar to home and small business users. ADSL iscalled “asymmetric” because most of its two-way or “duplex” bandwidth isdevoted to the downstream direction, sending data to the user. Only asmall portion of bandwidth is available for upstream or user-interactionmessages. However, most Internet and especially graphics- or multi-mediaintensive Web data need lots of downstream bandwidth, but user requestsand responses are small and require little upstream bandwidth. UsingADSL, up to 6.1 megabits per second of data can be sent downstream andup to 640 Kbps upstream. The high downstream bandwidth means that atelephone line may carry motion video, audio, and 3-D images todestination computers or television displays. In addition, a smallportion of the downstream bandwidth can be devoted to voice rather data,and phone conversations may be carried without requiring a separateline. Unlike a similar service over “cable” television lines, ADSL doesnot compete for bandwidth with neighbors in a given area. In many cases,your existing telephone lines will work with ADSL. In some areas, theymay need upgrading.

“CDSL” or “Consumer DSL” is a trademarked version of DSL, to be madeavailable by Rockwell Corporation, that is somewhat slower than ADSL (1Mbps downstream, generally predicted to be lower upstream) but has theadvantage that a “splitter” does not need to be installed at the user'send. Hardware may be required to carry CDSL by local phone companies tohomes or businesses. CDSL uses its own carrier technology rather thanDMT or CAP ADSL technology.

Various companies have worked with telephone companies in developing astandard and easier installation version of ADSL, called “G.Lite”, thatis believed to be under deployment at the time of this disclosure.“G.Lite” or “DSL Lite” (also known as “splitterless ADSL”, and“Universal ADSL”) is believed to be essentially a slower ADSL thatdoesn't require splitting of the line at the user end but manages tosplit it for the user remotely at the telephone company, which isbelieved to lower costs. G.Lite, officially ITU-T standard G-992.2, ispublished to provide a data rate from 1.544 Mbps to 6 Mpbs downstreamand from about 128 Kbps to about 384 Kbps upstream. At least onepublication has predicted G.Lite to become the most widely installedform of DSL.

“HDSL” or “High bit-rate DSL” is believed to be the earliest variationof DSL to be widely used for wideband digital transmission within acorporate site and between the telephone company and a customer. Themain characteristic of HDSL is that it is symmetrical: an equal amountof bandwidth is available in both directions. For this reason, themaximum data rate is generally lower than for ADSL. HDSL can carry asmuch on a single wire of twisted-pair as can be carried on a T1 line inNorth America or an E1 line in Europe (up to about 2.32 Mbps).

“IDSL” or “ISDN DSL” is somewhat of a misnomer since it's really closerto ISDN data rates and service at about 128 Kbps than compared with themuch higher rates generally associated with ADSL.

“RADSL” or “Rate-Adaptive DSL” is an ADSL technology to be madeavailable from Westell company in which software is able to determinethe rate at which signals can be transmitted on a given customer phoneline and adjust the delivery rate accordingly. Westell's “FlexCap2TM”version system uses RADSL to deliver from about 640 Kbps to about 2.2Mbps downstream and from about 272 Kbps to about 1.088 Mbps upstreamover an existing line.

“SDSL” or “Symmetric DSL” is similar to HDSL with a single twisted-pairline, carrying about 1.544 Mbps (U.S. and Canada) or about 2.048 Mbps(Europe) each direction on a duplex line. It's symmetric because thedata rate is the same in both directions. “UDSL” or “Unidirectional DSL”is a proposal from a European company, and is generally believed toprovide a unidirectional version of HDSL.

“VDSL” or “Very high data rate DSL” is believed to be a technology underdevelopment that promises much higher data rates over relatively shortdistances, for example between about 51 and about 55 Mbps over lines upto about 1,000 feet or about 300 meters in length. At least onepublication has predicted that VDSL may emerge somewhat after ADSL iswidely deployed and co-exist with it. The transmission technology (CAP,DMT, or other) and its effectiveness in some environments is not yetdetermined. A number of standards organizations are working on it.

“x2/DSL” is modem from 3Com that supports 56 Kbps modem communicationbut is upgradeable through new software installation to ADSL when itbecomes available in the user's area. At least one publication cites3Com as describing this technology to be “the last modem you will everneed.”

A “T1” transmission line is generally considered a “broadband” carrierand is defined as a type of “T-carrier” system, which is believed tohave been first introduced by the Bell System in the U.S. in the 1960'sas the first successful system that supported digitized voicetransmission. The T-carrier system is entirely digital, using pulse codemodulation and time-division multiplexing. Voice signals are typicallysampled at about 8,000 times a second and each sample is digitized intoan 8-bit word. With 24 channels digitized at the same time, a 192-bitframe, representing 8-bit words on each of 24 channels, is thustransmitted about 8,000 times a second. Each frame is separated from thenext by a single bit, resulting in a 193-bit block. The T-1's publisheddata rate of 1.544 Mbps generally represents the 192 bit frame, and the1-bit signaling bit, multiplied by 8,000.

A T-1 system typically uses 4 wires and provides duplex capability, withtwo wires dedicated for receiving and two for sending at the same time.The T-1 digital stream includes 24, 64 Kbps channels that aremultiplexed, wherein the standard 64 Kbps channel is based on thebandwidth required for a voice conversation. The four wires wereoriginally a pair of twisted pair copper wires, but more recent systemsprovide coaxial cable, optical fiber, digital microwave, and othercarrier technologies. The number and use of the channels may be variedfrom the standard guidelines.

The original transmission rate (1.544 Mbps) for T-1 lines is in commonuse today in Internet service provider (“ISP”) connections to theInternet. Another level, the T-3 line, is published to provide 44.736Mbps, and is also commonly used by Internet service providers. Anothercommonly used service is “fractional T-1”, which is the rental of someportion of the 24 channels in a T-1 line, with the other channelsunused.

Display Capabilities/Constraints & Related Standards

Various different types of receiver display capabilities may alsosignificantly impact the appropriate CODEC modality for efficientlycommunicating particular streaming media signals for display by thereceiver. A brief summary of certain examples to illustrate such varieddisplay parameters (e.g. resolution, clarity, color, depth, size,type/format-specific) is provided for a better understanding as follows.

One parameter that is highly variable between different types and makesof streaming media receiver devices, and therefore that may havesignificant impact on the appropriate CODEC to be used, is the range ofcolors that may be expressed by a display device, or “palette”. Astandard “browser-safe” palette, which may be accommodated by mostsoftware for Internet-based streaming media display, may include forexample about 216 colors, though for web-based streaming media thecomputer display capability as well as the browser software capabilitymust be understood.

With respect to computer display technology, a color is set for eachindividual pixel or addressable illumination element on the screen. Eachpixel has a red, green, and blue (RGB) component. By specifying theamount of intensity for each of these components, a distinct color isgiven to that pixel. A “true color” display generally defines the colorof a pixel on a display screen using a 24-bit value, allowing thepossibility of up to 16,777,216 possible colors. The number of bits usedto define a pixel's color shade is called the “bit-depth”. True color issometimes referred to as “24-bit color”, though many modern colordisplay systems offer a 32-bit color mode. An extra byte, called the“alpha channel”, is typically used for control and special effectsinformation. A “gray scale” (composed of discrete shades of gray)display setting is generally defined as having N bits of depth where Nrepresents the saturation of black within the pixel. If N=1, the imageis not called gray scale but instead monochrome, or black and white, asthe bit can only be on or off and can contain no shading information.

Common computer resolutions include for example and without limitationthe following:

-   -   (i) VGA or Video Graphics Array capable of displaying 640×480        pixels in 16 colors or 320×240 pixels in 256 colors in a 4:3        aspect ratio;    -   (ii) SVGA or Super Video Graphics Array capable of 800×600×6        bits/pixel (16 colors) or 650×480×8 bits/pixel (256 colors).        SVGA was created by the Video Electronics Association (VESA);        and    -   (iii) XGA (v1-4) or extended Graphics Array capable of 1024×768        pixels at 32,768 colors.

Additional standards have been added such as SXGA, defining pixel sizesabove 1960×1440 and color depths of 32 bits/pixel and higher.

In the event that a larger range of colors (or palette) is used by amedia signal than a particular display or browser can handle, mostbrowsers are typically adapted to “dither” the colors, which is hereinintended to mean that the browser will find colors within its palettethat it can substitute for any color that is outside of its palette. Tofurther illustrate the wide range of different system displaycapabilities, systems using Windows™ (commercially available fromMicrosoft Corporation) and Macintosh™ (commercially available from AppleCorporation) based operating systems do not have identical palettes;within the usual 256 color palette, 216 are common to both types ofbrowsers, whereas 40 are different and therefore require dithering by abrowser operating within one of the systems if an image signal iscommunicated to that type of system in a format specified by the other.

Many different technologies also exist with respect to how a visualdisplay is enabled from electronic information. The terms “VDT” or“Video Display Terminals” are generally used within the computerindustry and are herein intended to be used interchangeably with simplereferences to “display”. With respect to computer terminal use, VDT'scomprise a computer output surface and projecting mechanism that showstext and graphic images to the computer user. VDT's may use a variety ofspecific display technologies, including for example cathode ray tubes(“CRTs”), liquid crystal displays (“LCDs”), light-emitting diodes(“LEDs”), gas plasma, or other image projection technology. The displayis usually considered to include the screen or projection surface andthe device that produces the information on the screen. In somecomputers, the display is packaged in a separate unit or “monitor”, orthe display may be fully integrated in a single unit with the computerprocessor.

With respect to LCD's in particular, this technology generally requiresminimal volume and physical depth compared to other VDT's, and thereforeis typically used in laptop computers and cellphone/PDA's. LCD's consumemuch less power than LED and gas-display VDT's because they work on theprinciple generally of blocking light rather than emitting it. An LCDmay be either “passive matrix” or “active matrix”, which is also knownas “thin film transistor” or “TFT” display. The passive matrix LCD has agrid of conductors with pixels located at each intersection in the grid.A current is sent across two conductors on the grid to control the lightfor any pixel. An active matrix has a transistor located at each pixelintersection, requiring less current to control the luminance of apixel. For this reason, the current in an active matrix display can beswitched on and off more frequently, improving the screen refresh timeand therefore efficacy for higher speeds of streaming media (e.g. actionvideo). Some passive matrix LCD's have dual scanning, in that they scanthe grid twice with current in the same time as one scan in earlierversions; however, the active matrix is still generally considered to bethe superior technology of the two. Reflective color displaytechnology—the integration of color filters into passive-matrix displayconstruction—is a low-power, low-cost alternative to active-matrixtechnology. Because they reflect ambient light, reflective LCDs deliverparticularly high performance during use outside in daylight. Variousdifferent display technologies, and therefore transmission formats, havealso been specifically developed for television viewing. Thus severaldifferent standards have evolved for television transmission, and theirdifferences may significantly impact the nature and extent ofcompression desired (and therefore the choice of a particular CODEC) forcommunicating streaming media signals in television environs. Thesestandards include in particular and without limitation: standarddefinition television (“SDTV”); and high definition television (“HDTV”).

“SDTV” or “standard definition television” and “HDTV” or “highdefinition television” are the two categories of display formats fordigital television (“DTV”) transmissions, which are becoming thestandard. These formats provide a picture quality similar to digitalversatile disk (“DVD”), and are summarized relative to theirsimilarities and differences as follows.

HDTV provides a higher quality display, with a vertical resolutiondisplay from about 720p to at least about 1080i and an aspect ratio (thewidth to height ratio of the screen) of generally 16:9, for a viewingexperience similar to watching a movie. In comparison, SDTV has a rangeof lower resolutions and no defined aspect ratio. New television setswill be either HDTV-capable or SDTV-capable, with receivers that canconvert the signal to their native display format. SDTV, in common withHDTV, using the MPEG-2 file compression method in a manner thatgenerally reduces a digital signal from about 166 Mbps to about 3 Mbps.This allows broadcasters to transmit digital signals using existingcable, satellite, and terrestrial systems. MPEG-2 uses the lossycompression method, which means that the digital signal sent to thetelevision is compressed and some data is lost, but this lost data mayor may not affect how the human eye views the picture. Both the ATSC andDVB standards selected MPEG-2 for video compression and transport. TheMPEG-2 compression standard is elsewhere herein described in furtherdetail.

Because a compressed SDTV digital signal is smaller than a compressedHDTV signal, broadcasters can transmit up to five SDTV programssimultaneously instead of just one HDTV program, otherwise known as“multicasting”. Multicasting is an attractive feature because televisionstations can receive additional revenue from the additional advertisingthese extra programs provide.

With today's analog television system, only one program at a time can betransmitted. Note that this use of the term “multicasting” is distinctfrom its use in streaming video where it involves using specialaddressing techniques.

When the United States decided to make the transition from analogtelevision to DTV, the Federal Communications Commission decided to letbroadcasters decide whether to broadcast SDTV or HDTV programs. Mosthave decided to broadcast SDTV programs in the daytime and to broadcastHDTV programs during prime time broadcasting. Both SDTV and HDTV aresupported by the Digital Video Broadcasting (DTV) and AdvancedTelevision Systems Committee (ATSC) set of standards.

HDTV as a television display technology provides picture quality similarto 35 mm. movies with sound quality similar to that of today's compactdisc (further with respect to audio quality, HDTV receives, reproduces,and outputs Dolby Digital 5.1). Some television stations have beguntransmitting HDTV broadcasts to users on a limited number of channels.HDTV generally uses digital rather than analog signal transmission.However, in Japan, the first analog HDTV program was broadcast on Jun.3, 1989. The first image to appear was the Statue of Liberty and the NewYork Harbor. It required a 20 Mhz channel, which is why analog HDTVbroadcasting is not feasible in most countries.

HDTV provides a higher quality display than SDTV, with a verticalresolution display from 720p to 1080i. The p stands for progressivescanning, which means that each scan includes every line for a completepicture, and the i stands for interlaced scanning which means that eachscan includes alternate lines for half a picture. These rates translateinto a frame rate of up to 60 frames per second, twice that ofconventional television. One of HDTV's most prominent features is itswider aspect ratio (the width to height ratio of the screen) of 16:9, adevelopment based on a research-based belief that the viewer'sexperience is enhanced by screens that are wider. HDTV pixel numbersrange from one to two million, compared to SDTV's range of 300,000 toone million. New television sets will be either HDTV-capable orSDTV-capable, with receivers that can convert the signal to their nativedisplay format.

In the United States, the FCC has assigned broadcast channels for DTVtransmissions. In SDTV formats, DTV makes it possible to use thedesignated channels for multiple signals at current quality levelsinstead of single signals at HDTV levels, which would allow moreprogramming with the same bandwidth usage. Commercial and publicbroadcast stations are currently deciding exactly how they willimplement their use of HDTV.

Simulcast is the simultaneous transmission of the same televisionprogram in both an analog and a digital version using two differentchannels or frequencies. At the end of the DTV transition period, it isbelieved by that analog transmission will be substantially replaced suchthat current analog channels will be used solely for DTV. The extrachannels that were used for digital broadcasting may for example then beauctioned and used for more television channels or other services suchas datacasting. Simulcast is also used for the transmission ofsimultaneous television and Internet services, the transmission ofanalog and digital radio broadcasts, and the transmission of televisionprograms in different screen formats such as the traditional format andthe wide screen format. Simulcast broadcasting is used worldwide.

The transition to DTV is not an easy or inexpensive transition. For atelevision station to transmit DTV programming, it must build its DTVfacilities, but a station must have revenue to build these facilities.Simulcast allows stations to continue receiving revenues fromtraditional analog programming and also gain extra revenues from theextra digital programming. Another obstacle in the transition to DTV islack of interest among consumers. The need for special equipment isprohibiting viewers from seeing the difference between digital andanalog programs, which is also slowing down public enthusiasm for DTV.

The equipment needed for operating DTV depends on whether terrestrial,cable, or satellite services are used as the transmissionchannel/carrier. In any event, and according to known or anticipatedsystems, it is generally believed that consumers will, at a minimum,have to purchase a converter to view DTV transmissions on their oldtelevision sets. In addition, consumers that use terrestrial services orantennas to receive television signals need an antenna equipped fordigital signals. A consumer located in mountainous terrain in anATSC-compliant country may not be able to receive terrestrial-baseddigital signals because of multipath effects. This is common even withtoday's analog television system. In DVB compliant countries, terraindoes not affect the reception of digital signals. Satellite users arealready enjoying DTV broadcasting, but a larger satellite dish might beneeded to view HDTV programming.

A “set-top” box is herein defined as a device that enables a televisionset to become a user interface to the Internet and also enables ananalog television set to receive and decode DTV broadcasts. DTV set-topboxes are sometimes called receivers. It is estimated that 35 millionhomes will use digital set-top boxes by the end of 2006, the estimatedyear ending the transition to DTV.

A typical digital set-top box contains one or more microprocessors forrunning the operating system, usually Linux or Windows CE, and forparsing the MPEG transport stream. A set-top box also includes RAM, anMPEG decoder chip, and more chips for audio decoding and processing. Thecontents of a set-top box depend on the DTV standard used. DVB-compliantset-top boxes contain parts to decode COFDM transmissions whileATSC-compliant set-top boxes contain parts to decode VSB transmissions.More sophisticated set-top boxes contain a hard drive for storingrecorded television broadcasts, for storing downloaded software, and forother applications provided by the DTV service provider. Digital set-topboxes can be used for satellite and terrestrial DTV but are used mostlyfor cable television. A set-top box price ranges from $100 for basicfeatures to over $1,000 for a more sophisticated box.

In the Internet realm, a set-top box often really functions as aspecialized computer that can “talk to” the Internet—that is, itcontains a Web browser (which is really a Hypertext Transfer Protocolclient) and the Internet's main program, TCP/IP. The service to whichthe set-top box is attached may be through a telephone line as, forexample, with Web TV or through a cable TV company like TCI.

To take advantage of Dolby Digital 5.1 channel for satellite broadcasts,a satellite receiver that provides a Dolby Digital output is necessary.For cable users, all digital set-top boxes are equipped with a DolbyDigital two-channel decoder. To use 5.1 channel sound, a 5.1channel-compliant set-top box is needed or an external 5.1 channeldecoder unit.

The most dramatic demonstration of digital television's benefits isthrough a high-end HDTV, because of the larger screen, wider aspectratio and better resolution. Like most new technologies, however, HDTVis expensive. Nevertheless, less expensive digital TVs provide amarkedly improved viewing experience over regular TV, and for those whochoose to retain their old sets, even the addition of a set-topconverter will deliver a discernibly improved picture and sound.

The FCC's schedule for transition to DTV proposes that everyone in theU.S. should have access to DTV by 2002 and that the switch to digitaltransmission must be completed either by 2006 or when 85% of thehouseholds in a specific area have purchased digital television sets orset-top converters.

In the early 1990s, European broadcasters, consumer equipmentmanufacturers, and regulatory bodies formed the European Launching Group(ELG) which launched a “DVB” or “Digital Video Broadcasting” project inorder to introduce DTV throughout Europe. DVB is intended to provide anopen system as opposed to a closed system. Closed systems arecontent-provider specific, not expandable, and optimized only for thesystem they were developed for. An open system, such as DVB, allows thesubscriber to choose different content providers and allows integrationof PCs and televisions. DVB systems are intended to be optimized fortelevision, but as well as supporting home shopping and banking, privatenetwork broadcasting, and interactive viewing. DVB is intended to openthe possibilities of providing crystal-clear television programming totelevision sets in buses, cars, trains, and even hand-held televisions.DVB is also promoted as being beneficial to content providers becausethey can offer their services anywhere DVB is supported regardless ofgeographic location. They can also expand their services easily andinexpensively and ensure restricted access to subscribers reducing lostrevenues due to unauthorized viewing. Today, the DVB Project consists ofover 220 organizations in more than 29 countries worldwide and DVBbroadcast services are available in Europe, Africa, Asia, Australia, andparts of North and South America

Format-Specific Media

Various different formats for the streaming media signals themselves arealso herein summarized by way of non-limiting example to also provide afurther understanding of how CODECS may vary for a particular case.

“DVD” is an acronym for “digital versatile disc” is generally defined asa relatively recent optical disc technology that holds up to about 4.7Gigabytes of information on one of its two sides, or enough for a movieabout 133 minutes long on average. With two layers on each of its twosides, it may hold up to 17 Gigabytes of video, audio, or otherinformation, compared to current CD-ROM discs of approximately the samephysical size that hold about 600 Mbytes (DVD holds more than about 28times the information). DVD players are required to play DVD's, thoughthey will also play regular CD-ROM discs. DVDs can be recorded in any ofthree general formats variously optimized for: (i) video (e.g.continuous movies); (ii) audio (e.g. long playing music); and (iii) or amixture (e.g. interactive multimedia presentations). The DVD drive has atransfer rate somewhat faster than an 8-speed CD-ROM player. DVD formattypically uses the MPEG-2 file and compression standard, which has about4-times the resolution of MPEG-1 images and can be delivered at about 60interlaced fields per second where two fields constitute one image(MPEG-1 delvers about 30 non-interlaced frames per second. MPEG-2 and -1standards are elsewhere herein defined in more detail. Audio quality onDVD is comparable to that of current audio compact discs.

“DVD-Video” is the name typically given for the DVD format designed forfull-length movies and is a box that will work with a television set.“DVD-ROM” is a name given to the player that is believed by some to bethe future replacement to CD-ROM drives in computers, as these newerdrives are intended to play both regular CD-ROM discs as well as DVD-ROMdiscs. “DVD-RAM” is the name given to writeable versions of DVDs.“DVD-Audio” is the name typically given to players designed to replacethe compact disc player.

“VHS” is an acronym for “Video Home System” and is generally defined asa magnetic videotape cartridge format, typically a half-inch wide,developed for home use with the ability to record and playback analogvideo and audio signals. VHS has become a popular format and the defacto standard for home movie distribution and reproduction mainly dueto its pervasive presence and recordability. VHS stores signals as ananalog format on a magnetic tape using technology similar to that ofaudiocassettes. The tapes are played back and recorded on using VHSvideo cassette recorders (VHS VCRs). VHS tapes store up to around twohours of video typically, although some VCRs are able to record to themat a slower speed allowing up to six or even eight hours of recordingper tape.

The VHS format outputs a little over 200 lines of horizontal resolution.This compares to DVDs that output over 500 lines of horizontalresolution. Technically and perceptually, VHS is a format that has beensurpassed by other formats, including for example DVD, S-VHS, Hi-8 andothers. However, VHS remains a pervasive means for viewing video, andVHS tapes are still easily found across the country and around the worldeverywhere from movie rental stores to grocery stores making then easilyaccessible.

“CD” is an acronym for “compact disc” and is generally defined as small,portable, round medium for electronically recording, storing, and/orplaying audio, video, text, and other information in digital form.Initially, CD's were only read-only; however, newer versions allow forrecording as well (e.g. “CD-RW”).

“Super audio compact disc” or “SACD” is a high resolution audio CDformat that, together with DVD-Audio (“DVD-A”), are the two formatscompeting to replace the standard audio CD (though most of the industrygenerally is backing DVD-A, with a general exception believed to bePhilips and Sony). SACD, like DVD-A, offers 5.1 channel surround soundin addition to 2-channel stereo. Both formats improve the complexity ofsound by increasing the bit rate and the sample rate, and can be playedon existing CD players, although generally only at quality levelssimilar to those of traditional CDs. SACD uses Direct Stream Digital(“DSD”) recording, which is published as being proprietary to Sony, thatconverts an analog waveform to a 1-bit signal for direct recording,instead of the pulse code modulation (“PCM”) and filtering used bystandard CDs. DSD uses lossless compression and a sampling rate of about2.8 MHz to improve the complexity and realism of sound. SACD may alsoinclude additional information, such as text, graphics, and video clips.

Also for the purpose of further understanding, Internet-basedcommunications also have particular protocols for communication thatmust be accommodated by a streaming media communications system usingthe Internet “superhighway”. These protocols, in particular with respectto streaming media communication, are briefly summarized immediatelybelow for the purpose of providing a more detailed understanding.

With respect to Internet communication, streaming media signals aregenerally communicated in digital format via data packets. The terms“packets” are herein intended to mean units of data that are routedbetween an origin and a destination via the Internet or any otherpacket-switched network. More specifically, when a file is sent, theprotocol layer of the communications system (e.g. TCP layer of TCP/IPbased system) divides the file into chunks of efficient size forrouting. Each of these packets is separately numbered and includes theInternet address of the destination. The individual packets for a givenfile may travel different routs through the Internet. When they have allarrived, they are reassembled into the original file, for example by theTCP layer at the receiving end. A packet-switching scheme is anefficient way to handle transmissions on a connectionless network suchas the Internet. An alternative scheme, circuit-switched, is used fornetworks allocated generally for voice connections. Incircuit-switching, lines in the network are shared among many users aswith packet-switching, but each connection generally requires thededication of a particular path for the duration of the connection.

Wireless Communications & the WAP Gateway

Of equal importance to the contemporary age of the Internet, the age ofwireless communications has significantly extended society's ability tointeract outside of the fixed confines of the home and office, allowingour remote communications to break free from the umbilical cords ofwires and cables. For example, in 2000, the number of mobile subscribersgrew by close to 50%.

However, wireless communications systems, protocols, and enablingtechnologies have developed in a significantly fragmented,“format-specific” market on a world-wide scale. This is particularlytrue in comparing systems in wide use in the United States as comparedto the rest of the world. Therefore, much effort has been expended inovercoming compatibility issues between format-specific systems andbetween the related wireless devices operating on different platforms.For the purpose of further understanding wireless communication as it islater related to the present invention, the following is a briefoverview of significant technologies, systems, and protocols used in thewireless communication industry.

In general, the progression of wireless communications systems forcellular telephones is colloquially given the terms “1G”, “2G”, “2.5G”,and “3G”, representing respectively first generation, second generation,and so-on. Initial systems were purely analog, known as the 1G phonesand systems. However, with rapid growth, available bandwidth forcellular phone use quickly eroded, giving way to digital signalprocessing in the 2G, which significantly widened the availablebandwidth and ability for complex signal processing for advancedtelecommunications. However, as demand progressed for wireless Internetaccess, so went the technology development from 2G phones (generally notInternet enabled), to 2.5G and 3G (progressively more enabled). As willbe further developed immediately below, the systems, protocols, andenabling technologies thus have developed toward a concentrated focus inbringing the 2.5G and 3G modes to industry and consumers.

In general, there are four major digital wireless networks based upon 2Gtechnology: time division multiple access (“TDMA”), code divisionmultiple access (“CDMA”), Global System for Mobile communication (“GSM”)and cellular digital packet data (“CDPD”). These are briefly hereindescribed as follows.

Time division multiple access (“IDMA”) is a technology used in digitalcellular telephone communication that divides each cellular channel intothree time slots in order to increase the amount of data that can becarried. TDMA is used by Digital-American Mobile Phone Service (D-AMPS),Global System for Mobile communication (“GSM”), and Personal DigitalCellular (“PDC). However, each of these systems implements TDMA in asomewhat different and incompatible way. An alternative multiplexingscheme to TDMA and FDMA (frequency division multiple access) is codedivision multiple access (“CDMA”).

Code division multiple access (“CDMA”) refers to any of severalprotocols used in 2G and 3G wireless communications. As the termimplies, CDMA is a form of multiplexing that allows numerous signals tooccupy a single transmission channel, optimizing the use of availablebandwidth. The technology is used in ultra-high-frequency (UHF) cellulartelephone systems in the 800 MHz to 1.9 GHz bands. CDMA usesanalog-to-digital conversion (ADC) in combination with spread spectrumtechnology. Audio input is first digitized into binary elements. Thefrequency of the transmitted signal is then made to vary according to adefined pattern (code), so it can be intercepted only by a receiverwhose frequency response is programmed with the same code, so it followsexactly along with the transmitter frequency. There are trillions ofpossible frequency-sequencing codes, thus enhancing privacy and makingcloning difficult. The CDMA channel is nominally 1.23 MHz wide. CDMAnetworks use a scheme called “soft handoff”, which minimizes signalbreakup as a handset passes from one cell to another. The combination ofdigital and spread spectrum modes supports several times as many signalsper unit bandwidth as analog modes. CDMA is compatible with othercellular technologies; this allows for nationwide roaming.

The original CDMA, also known as CDMA One, was standardized in 1993 andis considered a 2G technology that is still common in cellulartelephones in the U.S. One version of cdmaOne, IS-95A, is a protocolthat employs a 1.25 MHz carrier and operates in RF bands at either 800MHz or 1.9 GHz; this supports data rates of up to 14.4 Kbps. Anotherversion, IS-95B, is capable of supporting speeds of up to 115 Kbps bybundling up to eight channels.

More recent CDMA varieties, CDMA2000 and wideband CDMA offer data speedsmany times faster. CDMA2000, also known as IMT-CDMA Multi-Carrier orIS-136, is a CDMA version of the IMT-2000 standard developed by theInternational Telecommunications Union (ITU). The CDMA2000 standard is a3G technology that is intended to support data communications at speedsranging from 144Kbps to 2 Mbps. Companies that have developed versionsof this standard include Ericsson and Qualcomm corporations. WidebandCDMA, or “WCDMA”, is an ITU standard derived from CDMA that is alsoknown as IMT-2000 direct spread. WCDMA is a 3G technology intended tosupport data rates of up to 2Mbps for local area access, or 384 Kbps forwide area access, and supports mobile/portable voice, images, data, andvideo communications at these speeds. WCDMA digitizes input signals andtransmits the digitized output in coded, spread-spectrum mode over a 5MHz wide carrier—a much broader range than the 200 KHz wide narrowbandCDMA.

The Global System for Mobile communication (“GSM”) is a digital mobiletelephone system that is widely used in Europe and other parts of theworld; this system uses a variation of “TDMA” (introduced immediatelybelow) and is the most widely used of the three digital wirelesstelephone technologies (TDMA, GSM, and CDMA). GSM digitizes, compresses,and then sends data down a channel with two other streams of user data,each in its own time slot. It operates at either the 900 Mhz or 1800 MHzfrequency band. At the time of this disclosure, GSM is generallyconsidered the wireless telephone standard in Europe, and has beenpublished to have over 120 million users worldwide and is available in120 countries. At least one company in the United States, AmericanPersonal Communications (Sprint™ subsidiary), is using GSM as thetechnology for a broadband personal communications services (“PCS”). PCSare telecommunications services that bundle voice communications,numeric and text messaging, voice-mail and various other features intoone device, service contract and bill. PCS are most often carried overdigital cellular links. This service is planned to have more than 400base stations for various compact mobile handsets that are being made bymanufacturers such as Ericsson, Motorola, and Nokia corporations; thesedevices generally include a phone, text pager, and answering machine.GSM is part of an evolution of wireless mobile telecommunications thatincludes High-Speed Circuit-Switched Data (HCSD), General Packet RadioSystem (GPRS), Enhanced Data GSM Environment (EDGE), and UniversalMobile Telecommunications Service (UMTS).

Cellular Digital Packet Data (“CDPD”) is a wireless standard providingtwo-way, 19.2 kbps packet data transmission over existing cellulartelephone channels.

Several different protocols have also been put into use forcommunicating over the various wireless networks. Various specific suchprotocols are briefly introduced as follows.

“X.25” is a packet-based protocol, principally used at the time of thisdisclosure in Europe and adapted as a standard by the ConsultativeCommittee for International telegraph and Telephone (CCITT). X.25 is acommonly used network protocol that allows computers on different publicnetworks (e.g. CompuServe, Tymnet, or TCP/IP network) to communicatethrough an intermediary computer at the network layer level. X.25'sprotocols correspond closely to the data-link and physical-layerprotocols defined in the Open Systems Interconnection (“OSI”).

“OSI” is a model of network architecture and a suite of protocols (aprotocol stack) to implement it, developed by ISO in 1978 as a frameworkfor international standards in heterogeneous computer networkarchitecture. The OSI architecture is split between seven layers, fromlowest to highest: (1) physical layer; (2) data link layer; (3) networklayer; (4) transport layer; (5) session layer; (6) presentation layer;and (7) application layer. Each layer uses the layer immediately belowit and provides a service to the layer above. In some implementations, alayer may itself be composed of sub-layers.

General Packet Radio Services (“GPRS”) is a packet-based wirelesscommunication service that promises data rates from 56 to 114 Kbps andcontinuous connection to the Internet for mobile phone and computerusers. The higher data rates will allow users to take part in videoconferences and interact with multimedia Web sites and similarapplications using mobile handheld devices as well as notebookcomputers. GPRS is based on Global System for Mobile (“GSM”)communication and will complement existing services such ascircuit-switched cellular phone connections and the Short MessageService (“SMS”). SMS is a message service offered by the GSM digitalcellular telephone system. Using SMS, a short alphanumeric message (160alphanumeric characters) can be sent to a mobile phone to be displayedthere, much like in an alphanumeric pager system. The message isbuffered by the GSM network until the phone becomes active.

The packet-based service of GPRS is publicized to cost users less thancircuit-switched services since communication channels are being used ona shared-use, as-packets-are-needed basis rather than dedicated only toone user at a time. It is also intended to make applications availableto mobile users because the faster data rate means that middlewarecurrently needed to adapt applications to the slower speed of wirelesssystems will no longer be needed. As GPRS becomes widely available,mobile users of a virtual private network (“VPN”) will be able to accessthe private network continuously rather than through a dial-upconnection. GPRS is also intended to complement “Bluetooth”, a standardfor replacing wired connections between devices with wireless radioconnections. In addition to the Internet Protocol (“IP”), GPRS supportsX.25 protocol. GPRS is also believed to be an evolutionary step towardEnhanced Data GSM Environment (“EDGE”) and Universal Mobile TelephoneService (“UMTS”).

Universal Mobile Telecommunications Service (“UMTS”) is intended to be a3G, broadband, packet-based transmission of text, digitized voice,video, and multimedia at data rates up to 2 Mbps. UMTS is also intendedto offer a consistent set of services to mobile computer and phone usersno matter where they are located in the world. This service is basedupon the GSM communication standard, and is endorsed by major standardsbodies and manufacturers, and is the planned standard for mobile usersaround the world by 2002. Once UMTS is fully implemented, computer andphone users can be constantly attached to the Internet as they travel.

Enhanced digital GSM enterprise (“EDGE”)service is a faster version ofthe Global System for Mobile (GSM) wireless service, designed to deliverdata at rates up to 384 Kbps and enable the delivery of multimedia andother broadband applications to mobile phone and computer users. TheEDGE standard is built on the existing GSM standard, using the sametime-division multiple access (TDMA) frame structure and existing cellarrangements. EDGE is expected to be commercially available in 2001. Itis regarded as an evolutionary standard on the way to Universal MobileTelecommunications Service (UMTS).

Wireless Application Protocol (“WAP”) is a specification for a set ofcommunication protocols to standardize the way that wireless devicessuch as cellular telephones and radio transceivers, can be used forInternet access, including e-mail, the World Wide Web, newsgroups, andInternet Relay Chat (“IRC”). While Internet access has been possibleprior to WAP, different manufactures have used “format-specific”technologies. WAP enables devices and service systems to intercooperate.

In most recent times, much effort has been expended to merge the fieldsof wireless communications and the Internet in order to bridge the gapof cords, wires, and cables that had before separated the “informationsuperhighway” from reaching people on wireless devices. Such technologymerger has developed for example within the home and office networksetting itself, where wireless infrared and radio frequencycommunications systems have been developed for interfacing equipmentwithin a “wireless” office or home. Another substantial effort has alsobeen underway to communicate and share information with more remotewireless devices, such as cell phones and personal digital assistants(“PDA's”).

PDA's are typically small, mobile devices that may be “hand-held” andusually contain limited processors and display screens for managing,storing, and displaying telephone books, calendars, calculator, and thelike. Recently available PDA's have been made “wireless enabled”, eitherby having wireless modems embedded within the PDA itself, or by couplingto wireless modem “plug-ins” such as a cell phone. Wireless enabledPDA's are also generally “Internet enabled” with limited “browser”capability allowing the PDA to communicate with server devices over theInternet. Examples of commercially available wireless “enabled” PDA'sinclude the Palm VII (from Palm, Inc.), and the iPAQ™ (from Compaq,Inc.). These PDA's include a Windows CE™ operating system that providesthe limited browser capability and screen display for content. Thesephones have processing capabilities from about 33 MHz to about 220 MHzand varied screen display capabilities, such as for example 320×240pixel screen displays.

Similarly, cellular phones themselves have also been recently rendered“Internet enabled”, also with limited browser capability and screens todisplay content. Examples of “Internet enabled” cellular phones include,for example: Sanyo SCP-4000™, Motorola i1000plus™, among a wide range ofothers; this wide field represents hundreds of different processing anddisplay capabilities.

In either the case of the PDA or the cellular phone that is“Intemet-enabled”, compatibility with the Internet protocols ofcommunication must be achieved. In general, wireless communications takeplace over a wireless applications protocol (“WAP”), whereascommunications over the Internet proceed according to one of severaldifferent protocols, the most common being Transmission ControlProtocol/Internet Protocol (“TCP/IP”). Therefore, a WAP Gateway, asshown in FIG. 1E, forms a bridge between the world of the Internet (orany other IP packet network) and the wireless phone/data network, whichare fundamentally different in their underlying technologies. Thegateway, in essence, does the interpretation between these two distinctentities, allowing the consumer to use their cell phone or hand heldcomputing device (e.g. PDA) to access the Internet wirelessly.

However, streaming media that is formatted for transmission to higherpower computing devices such as desk-top computers having significantdisplay capabilities is not generally compatible for receipt and viewingon these devices that have severely limited processing and displayfunctionality. Particular “format-specific” compression schemes havebeen developed for use specifically with only these devices, and onlyspecific media content may be transmitted to these devices in thoseformats.

There is still a need for a streaming media communications system thatis adapted to transmit a wide variety of streaming media signals inappropriate formats to be played by wireless devices such as cellularphones and PDA's having unique constraints, such as, for example,limited and variable processing, memory, and display capabilities.

SUMMARY OF THE INVENTION

The present invention addresses and overcomes the various limitations,inefficiencies, resource limitations, and incompatibilities of priorknown methods for streaming media communication, and is provided invarious beneficial modes, aspects, embodiments, and variations asfollows.

The present invention according to one embodiment is a streaming mediacommunications system that uses a computer implemented intelligencesystem, such as artificial intelligence, in a network system, such as aneural network, to communicate a streaming media signal between atransmission device and at least one destination device.

The present invention according to another embodiment is a system forcommunicating a streaming media signal between a transmission device anda plurality of destination devices each having different media signalprocessing capabilities.

The present invention according to another embodiment is a streamingmedia communications system that is adapted to communicate a streamingmedia signal from a single transmission device and at least onedestination device over a plurality of different transmission channels,each having a different transmission capability or constraints withrespect to communicating the streaming media signal.

The invention according to another embodiment is a neural networkincorporating an artificial intelligence implementation that is adaptedto be trained in an adaptive learning process with respect to theability of a streaming media compression system's ability to compress astreaming media signal at a source into a compressed representation ofthe streaming media signal, transmit the compressed representation overa transmission channel to a destination device, and decompress thecompressed representation into a decompressed representation of thestreaming media signal which is adapted to be played by the destinationdevice.

The invention according to another embodiment is a system forcompressing streaming media signals according to a CODEC that is used atleast in part based upon at least one parameter affecting communicationof the streaming media signals. According to one aspect of this mode,the CODEC is used according to at least one of the following parameters:a previously learned behavior of the CODEC with respect to anotherreference signal, a previously learned behavior of the CODEC withrespect to a prior attempt at compressing or decompressing the samestreaming media signal, a comparison of the CODEC's operation withrespect to the streaming media signal against a reference algorithmcompression of the streaming media signal, a learned constraint of thetransmission channel, and a learned constraint of the destinationdevice. In one beneficial embodiment, the CODEC is used based upon morethan one of these parameters, and in still a further beneficialvariation is used based upon all of the parameters.

The invention according to another embodiment is a system forcompressing streaming media signals using a CODEC library that isadapted to store multiple CODECS of different types and operations, andthat is adapted to be searched and accessed by a network system, such asa neural network, in order to provide an appropriate CODEC from theCODEC library for use in compressing the input streaming media signalinto a compressed representation for transmission to a destinationdevice.

The invention according to another embodiment is a CODEC operatingsystem that is adapted to interface with a CODEC Library and also with aneural network in order to use the neural network in a process, such asan artificial intelligence process, to choose an appropriate CODEC fromthe CODEC library and use the chosen CODEC for compressing the streamingmedia signal into a compressed representation of the streaming mediasignal for transmission to a destination device.

According to one aspect, the CODEC library is adapted to receive andstore a new CODEC such that the new CODEC may be interfaced with theneural network in order to be chosen and applied to compress thestreaming media signal as provided.

The invention according to another embodiment is a destination agentthat is adapted to be stored by a destination device for use indecompressing a compressed representation of a streaming media signal.The destination agent is adapted to communicate with a remotely located,compressed streaming media transmission system in order receive and playstreaming media signals therefrom. In a particularly beneficial aspect,the software agent is adapted to deliver information about thedestination device to the compressed streaming media transmissionsystem, and is also adapted to receive and decode certain encodedstreaming media signals from the compressed streaming media transmissionsystem.

The invention according to another embodiment is a system forcommunicating a streaming media signal having a destination agent thatis adapted to be stored within a destination device for decompressing acompressed representation of a streaming media signal into adecompressed representation that may be played by the destinationdevice.

According to one aspect of this embodiment, the destination agent has adiagnostic agent and also a decompression agent. The diagnostic agent isadapted to determine a value for at least one parameter of thedestination device related to the capability for processing, storage, ordisplay. The decompression agent is adapted to apply a CODECdecompressor to decompress the compressed representation of thestreaming media signal into the decompressed representation using aCODEC based at least in part upon the value of the at least oneparameter.

According to another aspect, the destination agent comprises a softwareagent. In one variation, the software agent is embedded within thedestination device. In another variation, the software agent is adaptedto be loaded onto the destination device at least in part by a remotelylocated source that is adapted to deliver the compressed representationof the streaming media signal to the destination device.

The invention according to another embodiment is a transcoder fortrancoding streaming media signals between at least one initial formatand at least one transcoded format. The transcoder includes a singlethread for each of several streaming media signals.

The invention according to another embodiment is a video-on-demandstreaming media system incorporating the embodiments shown in theFigures and otherwise described herein.

The invention according to another embodiment is a mobile telephonecommunications system incorporating the embodiments shown in the Figuresand otherwise described herein.

The invention according to another embodiment is an interactive gamingsystem incorporating the embodiments shown in the Figures and otherwisedescribed herein.

The invention according to another embodiment incorporates the variousmodes, embodiments, aspects, features, and variations herein disclosedabove and elsewhere to static media, as well as to media that is storedlocally after processing (e.g. compressing) and not transmitted.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1A-B show schematic block diagrams representing two respectivevariations of prior media communications systems using conventionalCODEC systems.

FIGS. 1C-D show schematic block diagramsrepresenting two respectivevariations of prior media transcoder systems.

FIG. 1E shows a schematic block flow diagram of the various interrelatedcomponents in a prior WAP gateway communications system.

FIGS. 2-3 show schematic block diagrams of the transcoder system of oneembodiment of the present invention during two respective modes of use.

FIGS. 4A-5 show block flow diagrams in various detail, respectively, ofa media communications system according one embodiment of the invention.

FIG. 6 shows a schematic block flow diagram of various interrelatedcomponents of a “video-on-demand” streaming video communications systemaccording one embodiment of the invention.

FIG. 7 shows a schematic block flow diagram of various interrelatedcomponents of a wireless streaming video communications system accordingto one embodiment of the present invention.

FIG. 8 shows a schematic block flow diagram of various interrelatedcomponents of a WAP gateway media communications system according oneembodiment of the present invention.

FIG. 9 shows a schematic block flow diagram of various interrelatedcomponents of a wireless communications system during backhaulingaccording to one particular mode of use of the media communicationssystem of an embodiment the present invention.

FIG. 10 shows a schematic block flow diagram of various interrelatedcomponents of an interactive gaming communications system and set-top TVbrowsing of one embodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The present invention as illustrated variously through the embodimentsbelow (and by reference to the Figures) provides a media communicationssystem that includes a compression system, a delivery system, and adecompression system, and in another aspect includes a transcodersystem. In general, the combination of these individual sub-systemsprovides a capability to efficiently transcode media between multipleencoding formats, in addition to customize the compression, delivery,and decompression of randomly selected streaming media signals basedupon a large array of system parameters as variables. These variablesinclude for example, without limitation, parameters related to thefollowing: the source video signal, the source transmitting device, thetransmission modality, and the destination device. The compression,delivery, and decompression of a media signal is thus customized to beoptimally efficient for a given, and changing, environment of use. As aresult, a wide range of complex streaming media signals may becommunicated with a level of efficiency and range of devicecompatibility that is significantly improved over other known systems.

Notwithstanding the benefits of the overall streaming mediacommunication system herein described, each sub-system described alsoindependently provides beneficially useful results for streaming mediacommunication. The various subsystems themselves, and the variousiterations of combinations of these sub-systems apparent to one ofordinary skill based at least in part upon this disclosure, are alsocontemplated within the scope of the invention. In addition, variousaspects of the overall communication system, as well as of eachsub-system described, are also contemplated as useful for otherapplications other than specifically for streaming media communicationin particular. Therefore, where apparent to one of ordinary skill, suchadditional applications are further contemplated within the scope of theinvention, despite the particularly useful modes applied to improvedstreaming media communication.

Transcoder

A video/audio transcoder 200 is provided according to the invention thatenables one incoming video source 210 to be streamed across multipleformats 215 (for example MPEG4, Real Video™, and QuickTime™) from onedevice without human intervention. The transcoder 200 according to thepresent embodiment provides substantially greater functionality at afraction of the price of other commercially available transcodersystems. Moreover, because the system works “on-the-fly,”pre-compressing of the video source 210 is significantly diminished.

More specifically, the transcoder 200 system and method according to theinvention is adapted to transcode digitized media originating from anycompressed or uncompressed format to be reproduced into any othercompressed format—on demand, real-time. The system 200 and method alsoenables efficient, simultaneous processing of multiple streams 215 ofdiffering data from a multiplicity of different compressed oruncompressed formats into a multiplicity of different compressedformats.

The transcoder 200 of the present embodiment is herein described in anoverall system by way of illustration by reference to FIG. 3. As shown,a first player initially makes a connection to a server 300 that housesthe transcoder 200. The player format (e.g., Microsoft Media),connection speed (e.g., 32 Kbps) and protocol (HTTP) are identified. Theserver 300 pulls the live or pre-encoded video into a “live buffer” or“cache” 310 and encodes it as digitized but nearly uncompressed data(e.g., AVI or MPEG2). The server 300 then loads an appropriate CODECthread (e.g. Microsoft Media™) at the connection speed (e.g. 32 Kbps).Next, the server 300 loads a HTTP/MS player thread that serves the firstclient Then, a second stream is requested by a client using M/S Playerat 100 Kbps with MMS. The server loads the appropriate MS CODEC threadat the appropriate 100 Kbps rate. Then, the server 300 loads an MMS/MSplayer thread to serve the second client. Then, a third stream isrequested by a client using Real Player at 40 Kbps with RTSP. The server300 loads the appropriate Real CODEC thread at the appropriate 40 Kbpsrate. Then, the server 300 loads an RTSP/Real player thread to serve thethird client. Again, this illustration is exemplary, and other specificCODECS may be suitable substitutes, as well as other bit-rates, etc.

In order to provide still a further understanding of the presenttranscoder embodiment, FIG. 3 shows the transcoder 200 by way of furtherexample as applied to serve multiple different video streams todifferent clients.

In brief, the present transcoder 200 shown and described uses “thread”communications instead of “IPC” or “Inter Processo Communications” thatare used according to many conventional transcoding techniques. For thepurpose of this transcoder 200 description, the term “thread” is hereinintended to mean an encapsulation of the flow of control in a program.Single-threaded programs are those that only execute one path throughtheir code “at a time”. Multithreaded programs may have several threadsrunning through different code paths “simultaneously”. In a typicalprocess in which multiple threads exist, zero or more threads mayactually be running at any one time. This depends on the number of CPUsthe computer on which the process is running, and also on how thethreads system is implemented. While a machine or system with a numberof n CPUs may be adapted to run no more than n threads in parallel, thethreading operation according to the present transcoder invention maygive the appearance of running many more than n “simultaneously” bysharing the CPUs among threads.

The transcoder 200 provides abstract APIs, and therefore the CODEC isaccessed without the (much larger) native encoder overhead. Buffering310 is created as a function of client pull for different video streams.Moreover, the transcoder 200 of the invention utilizes a networkarchitecture—a single thread for each different connection, combiningclients into same thread if they are at they are within the bufferedsegment of the same content. The transcoder's 200 use of threads in themanner herein shown and described is considered highly beneficialbecause a context switch between two threads in a single process isbelieved to be considerably cheaper (processing/memory/IO) than using acontext switch between two processes. In addition, the fact that alldata except for stack and registers are shared between threads makesthem a natural vehicle for implementing tasks that can be broken downinto subtasks that can be run cooperatively.

While various specific architectures may be built around the transcoder200 embodiments just described in order to achieve particularly desiredresults on a case-by-case basis. However, for the purpose of furtherillustration, the following is an example of a more detailed systemusing the transcoder 200 described. The transcoder 200 is providedadapted to support a large number of simultaneous customer streams, eachwith differing formats. In particular, such system may support more than5000 simultaneous streams, and in some circumstances more than 7000simultaneous customer streams, each with differing video formats. Stillfurther, the transcoder 200 may be implemented to convert any of a widenumber of video sources to a format uniquely appropriate or required formany different individual clients each having differing needs. In oneparticular example, a transcoder 200 as herein described may beimplemented to support such high demand simultaneously on any of thefollowing formats: MPEG 1; MPEG 2; MPEG 4; Motion JPEG; AVI; H.261;H.263; H.263+; RealVideo™ G-8; QuickTime™; Shockwave Flash™; IndeoCinepak™; ASF.

It is further contemplated that the transcoder 200 may be adapted in anoverall communication system to be compliant with all existing and soonanticipated fixed and mobile terminals and devices. Moreover, thetranscoder 200 may be implemented to adapt output stream formatvariables to dynamically accommodate the channel and platform conditionsof each client. Still further, the system incorporating the transcoderis adapted to support load balancing servers and routers formulti-transcoder installations. Accordingly, it is believed that thetranscoder 200 of the present invention delivers significantly greaterfunctionality for significantly lower cost than other prior transcodingtechniques and systems.

As described above, various different system architectures mayincorporate the transcoder 200 of the invention without departing fromthe scope of the invention. However, more details of a particulararchitecture that is believed to suitably provide the beneficial levelof support just described includes the following aspects: (i) dualP3-933 processor; (ii) any variant of Unix OS; (iii) 512 MB RAM;Redundant Firewire or Gigabit Ethernet; Redundant Power Supplies. Suchsystem may be provided in a rack mounted configuration, or otherwise tosuit a particular need.

The following aspects of the transcoder 200 of the invention should becontemplated as broadly beneficial, both independently and in variouscombinations as is apparent to one of ordinary skill based at least inpart from this disclosure.

A system and method is provided for utilizing asynchronous softwarethread communication in both user and kernel space to perform efficienttranscoding on multiprocessor and/or distributed computing platforms(such as clustering). It has been observed that this method is moreefficient than utilizing traditional IPC methods to implement thetranscoder. A shared library of CODEC algorithms is created and used toaccess the various CODEC algorithms, thereby incurring a lowerprocessing overhead as well as lower memory utilization than thatrequired by the traditional combined encoder functionality such as thatused in the majority of commercial encoders. Of particular benefit,common threads may be used for multiple connections, and in fact even asingle thread may be used for every individual connection using thepresent transcoder.

A system and method is also provided for combining multiple clients tobe served by the same thread (for efficiency) whenever the same contentis demanded and dynamic buffers (caches) can accommodate all of the datapoints demanded.

Media Compression and Delivery System

A data compression and delivery system 400 and method is also providedaccording to the invention for real time dynamic data signal processingfor optimal reproduction of approximations of original media data over agiven set of constraints. This system 400 and method is illustratedschematically by way of block flow diagrams in FIGS. 4A and 5. Furtherdescription of the various beneficial features and operation of thissystem is provided as follows by way of exemplary embodiments generallyincorporating by reference the description provided by these FIGS. 4A-5.

FIG. 4A is a block diagram illustration of one embodiment of the datacompression and delivery system 400 of the present invention. As shownin FIG. 4A, the data compression and delivery system 400 comprises mediamodule 405, dynamic player module 407, image processor 410, baselinesnapshot module 415, classifier 417, quality of standard (QoS) module420, network layer input module 425 and network output layer module 430.The system 400 further comprises a neural network processing module 440,timer 435, CODEC library module 445, dynamic client request module 450,ICMP module 455, device and network parameters measurement module 460and delivery and transmit module 465.

In one embodiment, the system 400, resident at a server node(s),processes incoming uncompressed or previously compressed data. Thesystem 400 employs neural networks 440 with artificial intelligence tomonitor the incoming data to determine a plurality of keycharacteristics of each data segment. The system 400 correlates theincoming data characteristics with libraries 445 of pre-developedself-referencing experientially learned rules of the patterns in a scenein a sequence of frames in the input signal (e.g., a video signal) andwith externally imposed constraints to optimally choose a preferredcommercially available compression/decompression algorithm (e.g. CODEC)for each segment of the data. The system 400 then sets up an extensivearray of usage controls, parameters and variables to optimize the chosenalgorithm. Choice of algorithm and set up of parameters and variableswill dynamically vary with each segment of incoming data depending uponthe characteristics of the data as well as the evolving optimizationprocess itself. The set of possible algorithms is numerous, limited onlyby availability and other commercial considerations. Each segment ofdata is encoded and compressed in the above manner and then served to acommunications channel.

The compression system 400 just described is particularly useful as astreaming media compression engine, which, based upon information fromthe available CODEC's and the streaming media delivery system, performsframe-by-frame analysis of the incoming video using another artificiallyintelligent neural network 440. The system 400 then chooses the mostappropriate compression format and configures the compression parametersfor optimal video compression based on the best quality as measured by,in one embodiment, a selection of a peak signal to noise ratio from theunderlying system environment. The result is the “optimal” video andaudio service for the device and conditions present.

A more specific account of the artificial intelligence/neural network440 aspect of this system as applied to streaming media signals isprovided as follows. Initially, a library of separate and distinctCODECs are added to the system as a searchable CODEC library 445.Additional libraries of relevant reference information are alsoprovided, including: a Network Transport Standards (NTS) library 443;and a Quality-of-Service (QoS) library 447. Then, a video (media source)is introduced either in a digitized or non-digitized format (ADconversion is used) via image processor 410. Image processor 410 thendecompresses the source (if required) and employs various standard imageprocessing algorithms used for “cleaning-up” the source image(s). Theresultant source media is then passed to the baseline snapshot 415repository where it will be used as a “perfect gold standard” for latercomparison. Simultaneously, this resultant source media is also fed tothe classifier 417.

The classifier 417 analyzes the source media for temporal, spatial andlogical features for the purpose of creating source media sub-segmentswhich exhibit similar combinations of temporal, spatial and logicalfeatures. “Similar” is defined to mean a contiguous sub-segment of thesource media that contains common temporal, spatial and logical featuresthat would lend themselves to a particular encoding/compressionalgorithm (as found in the CODEC library 445). This source mediasub-segment (or, in one embodiment, a group of contiguous video andaudio frames) is referred to as a “scene”.

The neural network process 440 then operates upon this scene byemploying CODECs from the CODEC library 445 to compress the scene. Theinternal configuration of each CODEC are manipulated/changed inaccordance with inputs obtained from the NTS library 443, QoS library447, Timer Process 435, Network layer Input 425, ICMP agent 455 and theDevice and Network Parameter measurement agent 460. The compressed sceneis then decompressed and a comparison is made against the BaselineSnapshot 415 using a quality measurement made by the quality standardprocess 420. In one embodiment of the present invention, the QualityStandard Process 420 employs a peak signal to noise ratio (PSNR)algorithm in order to perform the comparison of the decompressed sceneagainst the baseline snapshot of the source media. The comparisonprocess is repeated with various CODECs from the CODEC library 445 untilthe Neural Network Process 440 is satisfied with the quality of theresultant compressed scene, within the constraints of the inputsreceived from the NTS library 443, QoS library 447, Timer process 435,Network Layer Input 425, ICMP Agent 455 and the Device and NetworkParameter Measurement Agent 460. Finally, the resultant compressed sceneis sent to the Network Layer Output 430 which transports the compressedscene to the Client using an appropriate Network Transport protocol andQoS algorithm.

The above process is repeated until the entire source media has beentransmitted to the Client or until the process is aborted due to variouspossible conditions which may include: a Client request to abort,network transport failure, Client hardware failure, etc.

The NTS library 443 is a repository of network transport services thatare selected and used by the Network layer output 430 to transportcompressed source media to the Client and by the Network Layer Input 425to receive information from the Client. The selection is based uponqualitative and quantitative inputs received from the Network LayerInput 425, ICMP agent 445 and the Device and Network ParameterMeasurement agent 460.

The QoS library 447 is a repository of quality of service algorithmsthat are selected and used by the network layer output 430 to transportcompressed source media to the Client. The selection is based uponqualitative and quantitative inputs received from the Network LayerInput 425, ICMP agent 455 and the Device and Network ParameterMeasurement agent 460.

The ICMP agent 455 generates inputs to the neural network process 440that dynamically provides it with the quantitative and qualitativecharacteristics of the transport in use between the processor and theclient. In one embodiment of the present invention, the ICMP protocol isused for this purpose.

The Device and Network Parameters Measurement agent 460 generates inputsto the neural network process 440 that dynamically provides it with thequalitative and quantitative characteristics of the client'senvironment. In one embodiment of the present invention, these clientenvironment characteristics include central processing unit (CPU)capacity, network interface characteristics, storage capacity and mediarendering devices capabilities.

Still referring to FIG. 4A, the Network Layer Input 425 provides inbound(originating from the client) network transport services. The NetworkLayer Output 430 provides outbound (originating from the processor)network transport services. The Timer Process 435 provides a way for theuser of the invention to limit the maximum amount of time that theNeural Network Process 440 will spend in processing a given sourcemedia.

FIG. 4B is a block diagram illustration of one embodiment of a CODECselection scheme of the neural network processing module 440 of oneembodiment of the present invention. The neural network processingmodule 440 shown in FIG. 4B comprises a video frame selection module475, CODEC parameters module 480, input layer module 485, hidden layers486-487 and output module 488. In one embodiment of the presentinvention, a CODEC representative signal suitable to be used as areference baseline signal for incoming signals to the neural networkprocessing module 440 is generated by the neural network processingmodule 440. In one embodiment, the classifier 417 determines whichscenes in segments of an incoming video signal represents the best scenein light of the available parameters of the underlying CODEC. A list ofstandards are used by the neural network processing module 440 todetermine which scene in the signal represents the best scene. In oneembodiment, the Neural Network Process 440 samples a number of pixels ina particular frame of video to determine changes in the number of pixelsin that particular frame vis-a-vis the pre-determined parameters of thevideo signal. In another embodiment, significant motion changes in aparticular scene in the video signal may be used as the baselinereference scene (“best scene”) for subsequent incoming video.

In one embodiment of the present invention, the neural networkprocessing module 440 takes a segment of video from the classifier 417as an input and subsequently takes a sample of this input to deriveenough information that characterizes the video signal. For example, inthe scheme illustrated in FIG. 4B, the Neural Network Process 440 takesa window snap-shot (e.g., a 176×144 pixel window) to examine. It isadvantageous for the Neural Network Process 440 to look at the center ofthe sample window to generate enough information about the video signal.In one embodiment of the present invention, the Neural Network Process440 uses a minimum of 8 frames to generate the requisite informationabout the video signal. Information from the sample window is presentedwith the particular CODEC parameters from parameter module 480 to theinput layer 485.

The input layer 485 is coupled to a plurality of hidden layers 486-487via a plurality of neurons with each connection forming either a strongor weak synoptic link from one neuron to the other. In one embodiment,each CODEC supported by the neural network processing module 440 isprovided with its own neural network to process the CODEC specificparameters that come with the particular CODEC. The Neural NetworkProcess 440 generates the “best” video signal through a round-robin likeprocess referred to as a “bake-off” from the plurality of CODECsprocessed during a video sampling capture period. In processing the bestvideo representation from incoming signals, each of the correspondingneural networks for each of the CODECS generates the best representativesample from the hidden layers 486-487 and feed the signal to the outputmodule 488. In one embodiment of the present invention, the output dataset of the best CODEC from each class of CODECS being processed by theNeural Network Process 440 has two possibilities. The first being theNeural Network Process 440 submitting the best results for each CODEC tothe output module 488 to a “bake-off” neural network of the plurality of“best” samples for each of the plurality of CODECS which in turngenerates the winning best CODEC from the plurality of best CODECS. Thebake-off neural network is smaller and faster than the neural networksthat handle the processing of the CODECS.

In a second processing scheme, the Neural Network Process 440 mayimplement a genetic algorithm processing of the best CODECS generated bythe plurality of CODECS. The genetic algorithm follows the samestatistical selection approach of a marble game. Thus, instead offeeding the winning output CODEC from the various neural networks into a“bake-off” neural network, a genetic algorithm processing may be appliedto feed the output module 488 from the various neural networks into abucket and picking the best CODEC representation from a collection ofscenes at the end of the source media, for example, a movie, etc. In oneembodiment of the present invention, the Neural Network Process 440 usesa combination of forward and backward propagating algorithm to processthe CODECS.

Referring back to FIG. 4A, for the purpose of providing a furtherunderstanding of this artificial intelligence process, the followingexample of one particular application is provided. It is to beappreciated that the features and operation of the system provided bythis exemplary application are to be considered as broadly descriptiveof the neural network 440 aspect for data compression and deliveryaccording to the invention. Other applications may be made and fallwithin the scope of the invention.

A video content provider installs the system of the present invention onits server. Sample videos are introduced to the system in order toperform an initial AI process as described above. A complex matrix ofCODEC characterizations, e.g. for each bit rate, pattern of video, etc.,is created to be drawn from later. Next, a client end-user connects tothe content provider system in order to view a video M. Thecommunication system of the invention residing on the server delivers asoftware agent to the client's device, thus enabling the client toconnect to the communication system in order to deliver device-specificinformation and receive the appropriate compressed signal withdecompression CODEC for playing. Next, the AI system begins loading thevideo M as a streaming signal into a buffer for the purpose of choosingthe appropriate CODEC for each frame and compressing each frameappropriately for transmission. The time period of the buffer dependsupon multiple variables, principally the processing power of the system,and may be generally for example approximately 15 seconds for systemshaving appropriate capability for pre-recorded but uncompressed videomedia. Within the buffer, each frame is compared against each CODECaccording to the “types” of sequences pre-tested in matrix as depictedin the diagram.

Next, the system 400 looks at end-user parameters, e.g. screenresolution, memory available, via information received from the softwareagent in the client's device. The most appropriate CODEC is then chosenand configured/tuned for optimal performance by setting certainvariables within the CODEC to fixed quantities (e.g. based on comparingsource video vs. patterns in past, transmission channel capabilities orconstraints, and destination device capabilities or constraints). Theprocess just described is generally done frame-by-frame by theclassifier 417, but the CODECS are compared for temporal compressionefficiency such that the process for each frame contemplates otherleading and lagging frames. Once the appropriate CODEC is chosen andtuned for each frame (or block of frames where appropriately determinedautomatically by the system), the delivery system reports to the clientagent and delivers the tuned CODEC ahead of the corresponding frame(s)to be decompressed and played.

It is to be appreciated that the neural network 440 of this system 400continuously learns and remembers the performance and operation of theCODECS within the CODEC library 445, and continuously uses its learningto improve the compression efficiency of the input media signal. Theprocess of running a signal frame through the library, modifying CODECoperating parameters, comparing compression performance by the comparelogic 525 (FIG. 5) against reference standard compression, and runningthe loop again with further modifications, is an iterative 550 (FIG. 5)one that generally continues to improve compression efficiency. In fact,compression with one or more CODECS in the library 445 may reachimproved levels better than the reference compression algorithm(s).

Nevertheless, when time constraints 435 (FIG. 4A) are present (such asin real-time push or pull demand for the streaming media content), thisprocess must eventually be stopped at some point so that a particularframe or series of frames being processed may be compressed 575 anddelivered 580 to the destination without unacceptable delay by timer435. Then, the next frame or series may be operated upon by the neuralnetwork 440 within the CODEC operating system. These endpoints may bedefined by reaching a predetermined desired result, such as for examplebut without limitation: (i) reaching a predetermined percentage (%)compression efficiency, such as for example as compared to the referencestandard; or (ii) reaching a predetermined or imposed time limit set onthe process, such as for example according to a time related to thebuffer time (e.g. 15 seconds); or (iii) the earlier occurrence of either(i) or (ii). In any event, though an endpoint is reached for choosingthe appropriate CODEC and performing the compression 575 and delivery580 operations, this does not mark an endpoint for the neural network440 training which continues. The information that is gathered througheach loop in the process is stored 550. When subsequent similar framesor system constraint parameters in an incoming frame are encountered 545in the future, the stored information is remembered and retrieved by theneural network 440 for improving compression 575 and delivery 580efficiency.

While many different communication protocols are contemplated, oneparticular embodiment which is believed to be beneficial uses a “fullduplex network stack” protocol, which allows for bi-directionalcommunication between the server and the client device. Again, whileother protocols may be appropriate for a particular application, thefull duplex system is preferred.

The system 400 just described addresses the difficulties encounteredwith previously known CODEC systems by utilizing the streaming mediadelivery architecture to overcome latency issues and the embedded neuralnetwork 440 to overcome speed concerns. The system 400 is then able toreconfigure the algorithms used for compression in the neural network440, the goal being to achieve optimum results every time over anynetwork configuration.

A wide variety of CODECS may be used within the CODEC library 445according to the overall compression systems and methods just described,though beneficial use of any particular CODEC according to the inventioncontemplates such CODEC taken either alone or in combination with otherCODECS. For example, an appropriate CODEC library 445 may include one ormore of the following types of CODECS: (i) block CODECS (e.g. MPEGversions, such as Microsoft Media™ or QuickTime™); (ii) fractal CODECS;and (iii) wavelet CODECS (e.g. Real™). According to another aspect, anappropriate CODEC library 445 may include one or more of the followingtypes of CODECS: (i) motion predictive CODECS; and (ii) still CODECS.Still further, the CODEC library 445 may contain one or more of thefollowing: (i) lossy CODECS; and (ii) lossless CODECS.

In one embodiment of the present invention, all of these different typesof CODECS may be represented by the CODEC library 445 according to theinvention; and, more than one particular CODEC of a given type may beincluded in the library. Or, various combinations of these various typesmay be provided in order to achieve the desired ability to optimizecompression of a streaming media communication over a wide range ofreal-time variables in the signal itself, transmission channelconstraints, or destination device constraints. Still further, anadditional highly beneficial aspect of the invention allows for newCODECS to be loaded into the library 445 and immediately available foruse in the neural network 440 compression/delivery system 400.Nevertheless, one particular example of a CODEC library 445 which isbelieved to be beneficial for use in optimally communicating a widerange of anticipated streaming media signals, and of particular benefitfor image signals, includes the following specific CODECS: MPEG versions1, 2, and 4 (e.g. Microsoft Media™ and QuickTime™); DUCK TruMotion™;ON2; Real Media™; MJPEG: H.261; H.263; H.263+; GIF; JPEG; JPEG2000; BMP;WBMP; DIVX.

The following are further examples of various aspects of the compressionsystem and method just described that should be considered as broadlybeneficial, both independently and in various combinations as isapparent to one of ordinary skill based at least in part on thisdisclosure. Further examples of such broad aspects are elsewhereprovided in the “Summary of the Invention” as well as in the appendedclaims.

Use of neural networks 440 with artificial intelligence to achieve thevarious CODEC operations described is broadly and uniquely beneficial.In particular, a system and method is provided for pre-processing 410 ofsource data determined by application of learned responses to the signalquality, data content and format of the data. A system and method isprovided for processing each unit (e.g. frame or block of frames) ofsource data by selection and application of a suitable CODEC (from a setof all available CODECS in the CODEC library 445) dependent uponobserved characteristics of the source data and application ofpast-learned responses to compressing similar data. A system and methodis provided for processing each unit of source data by setting amultiplicity of compression characteristics within a chosen compressionalgorithm to optimize capture and preservation of the original dataintegrity. Still further, each or all of the aforementioned signalprocessing steps is applied to each unique, sequential unit of signaldata, e.g., signal clip, video frame, or individual packet asappropriate.

It is further contemplated that a CODEC management system 400 accordingto the invention provides a system and method for image processing thatis adapted to normalize original source data/images as well as to resizeand resample original data to fit the specification of the neuralnetwork processing module 440. An ability to serve any transmission orrecording channel with a single system and with any source data streamis also provided. Moreover, the various systems and methods hereindescribed, individually and beneficially in combination, are providedwith compatibility to any connection or connectionless protocol,including but not limited to TCP, UDP, WTP/WDP, HTTP, etc.

The invention as herein shown and described also allows for highlybeneficial applications for accelerating the learning rate of neuralnetworks 440 while minimizing the data storage requirements to implementsaid networks. Different classes of data streams each have uniquecharacteristics that require substantially greater processing by neuralnetworks 440. For example, video data streams differ by prevalence anddegree of motion, color contrast, and pattern and visibility of details.Greater processing requires longer times to reach optimal functionality.Greater processing also requires more predictive library storage, oftengrowing to unlimitedly large sizes. For real-time neural networkprocessing, processing time and storage can be minimized to greatlyincrease functionality by providing pre-developed predictive librariescharacteristic of the class of data stream.

Accordingly, the following are examples of aspects of the pre-trainedneural network 440 aspects of the invention that should be appreciatedas broadly beneficial, both independently and in combination (includingin combination with other embodiments elsewhere herein shown anddescribed). A system and method is provided that creates and usesartificial intelligence in a neural network 440 and pre-trains thatintelligent network for use in solving a problem, which problem may befor example but not necessarily limited to streaming media compressionaccording to a particular beneficial aspect of the invention. A systemand method is also provided for subdividing the universe of problems tobe solved into useful classes that may be processed according to alearned history by the intelligent network.

An intelligent streaming media delivery system and method is alsoprovided according to the invention that manages content transmissionbased on end-user capabilities and transmission channel constraints,such as for example, but without limitation, available transmissionspeeds or bandwidth, and Internet congestion. The data compression anddelivery system 400 utilizes a computer implemented intelligenceprocess, such as an artificial intelligence process based on a neuralnetwork to analyze aspects of the connection (including withoutlimitation differing bit rates, latencies, transmission characteristicsand device limitations) to make modifications in the compressionmethodology and to manage Quality of Service (“QoS”) 420 issues.Compressed, digital, restorable and/or decompressible data streams maybe therefore delivered to a multiplicity of different local and/orremote devices via a multiplicity of transmission mediums characterizedby differing capabilities. In addition, a decompression system isprovided for reproducing the decompressed data at the terminal device.

In one beneficial embodiment, a terminal device establishes a link withthe system resident on a server node(s). Except for software normallyrequired to establish communications, the terminal device might notinitially have resident software embedded therein associated with thepresent system. Upon linking the terminal device to the server node, thesystem transmits a software agent to the terminal device that cooperateswith other software modules on the server-side that together form theoverall delivery system. The software agent informs the system of theterminal device configuration and processing capacities fordecompressing and displaying the data. The software agent also reportscertain relevant information to the system of the characteristics of thecommunication channel between the terminal and the server. Suchinformation includes, without limitation: latency, bandwidth, and signalpath integrity. Based upon terminal device configuration and real timeupdates of channel characteristics and capabilities, the system activelymanages transmission of the compressed data stream by varying parameterssuch as buffer length, transmitted bit rate, and error correction. Thesystem also feeds operating conditions to the compression system todynamically alter encoding and compression settings to optimize deliveryof the data. The delivery software agent resident on the terminal devicedecompresses the data stream that is composed of segment-by-segmentvariations in compression/decompression algorithm and settings thereof.Dependent upon the terminal device configuration, and especially forvery thin clients, instructions may be refreshed on a segment-by-segmentbasis for each decompression algorithm and encoding setting combination.Instructions for decompressing may also be kept resident if appropriateto the terminal device.

The software agent described for transmission to and operation by thedestination device is therefore also considered a highly beneficialaspect of the compression/delivery systems and methods described. Bydelivering the software agent to the device from the source, a widerange of existing destination devices may be used for communicationaccording to methods that may include variable uses of one or morealgorithms or other operations at the transmission source. In otherwords, the destination devices may not be required to be“format-specific” players as is required by much of the conventionalstreaming and static media communication systems. Also, by providing thedestination agent with a diagnostic capability, diagnostic informationmay be gathered at the destination device and transmitted back to thesource in a format that is compliant for use by the source in its neuralnetwork process for achieving the proper CODEC operation for a given setof circumstances.

The use of a client-side agent to supply quality of service informationincluding client-side device data and communication channel status inreal time is therefore also believed to be broadly beneficial beyond thespecific applications and combinations of other aspects of the inventionalso herein provided. In addition, the processing of each unit ofcompressed, transmission-ready data to accommodate client-side deviceand real-time communication channel conditions is also broadlycontemplated as having broad-reaching benefits. Still further, a systemand method is described that provides instructions to a client-sideagent to enable decompression of each sequential, uniquely compressedunit of data. Therefore, another broad benefit of the invention providesa destination device (such as from the transmission source as hereindescribed for the particular embodiments) with a CODEC that is adaptedto decompress a compressed representation of an original media signalinto a decompressed representation based upon variable parametersrelated to at least one of the following: aspects of the original mediasignal, transmission channel constraints, and destination deviceconstraints. In another broad aspect, the destination device is adaptedto use a CODEC that is chosen from a library of CODECS based upon aparameter related to an aspect of the original media signal.

The systems and methods herein described are also considered applicableto the signal processing of each unique, sequential unit of signal data,e.g., signal clip, video frame, or individual packet as appropriate. Inaddition, the system and its various sub-systems may also be purelysoftware that must be loaded into each appropriate device, or it may beembedded in a host hardware component or chip, e.g. on the server side,or in certain circumstances, on the client side (e.g. various aspects ofthe destination agent), or for example may be stored such as in flashmemory.

The various aspects of the media compression system and method justdescribed are considered beneficial for use according to a wide range ofknown and soon anticipated media communication needs, including forexample according to the various communications devices,communication/transmission channel formats and standards, and mediatypes and formats elsewhere herein described (e.g. in the “Background”section above).

However, for the purpose of further understanding, FIG. 6 shows aschematic view of the overall streaming media communications system 600as specifically applied to “video-on-demand” aspects according to oneembodiment of the present invention, wherein many different end users610-620 at many different locations may request and receive, real-time(e.g. without substantial delay), pre-recorded video from a remotesource. Further to the information provided in FIG. 6, at least onespecific implementation of the media communication system 600 deliversthe following types of video at the following bit-rates (denotescompressed representations of original signals that are convertible by adestination device to decompressed representations having no orinsubstantial loss as observed by the eye of the typical humanobserver): VHS-format video as low as about 250 Kbs; DVD-format video atabout 400 Kbps; and HDTV-format video at about 900 Kbps. According tothese speeds, it is believed that video-on-demand may be provided bytelephone carriers over resident transmission line channels, such forexample over existing DSL lines 630-640.

However, as available bandwidth and mass communication continue topresent issues, it is believed that even greater efficiencies may beachieved resulting in delivery of compressed representations of thesetypes of video signals at even lower bit rates. Again, as elsewhereherein described, the compression efficiencies of the invention areclosely related to and improve as a function of the processing powermade available to the neural network 440, and the neural network's 440continued learning and training with respect to varied types of media.These resources may even make more remarkable compression efficienciesachievable without modification to the fundamental features of thepresent invention.

Therefore, the following are further examples of transmission rates forcertain compressed video signals that are believed to be desirable andachievable according to one embodiment of the invention: VHS-formatvideo as low as about 200 Kbps, more preferably as low as about 150Kbps, and still more preferably as low as about 100 Kbps; DVD-formatvideo as low as about 350 Kbps, more preferably as low as about 300Kbps, and still more preferably as low as about 250 Kbps; andHDTV-format video as low as about 800 Kbps, and still more preferably aslow as about 700 Kbps.

Moreover, at least one implementation of the media communications system400 of one embodiment of the invention delivers 20-24 frames/sec colorvideo at a transmission rate of 7 Kbps. This is believed to enablesubstantial advances in communication of streaming media signals via towireless destination devices via the WAP Gateway, as is furtherdeveloped elsewhere hereunder.

It is also to be appreciated that, while video communication has beenemphasized in this disclosure, other types of streaming or static mediaare also contemplated. For example, at least one implementation of thecompression and delivery embodiments has been observed to providesubstantially CD-quality sound (e.g. via compressed representations oforiginal signals that are convertible by a destination device todecompressed representations having no or insubstantial loss as observedby the ear of the typical human observer) at a bit-rate of about 24Kbps. At these rates, audiophile-quality sound may be delivered forplaying over dial-up modems. However, with further regard to availableresource commitment and extent of neural network training, it is furthercontemplated that the invention is adapted to deliver CD-quality soundat speeds as low as about 20 Kbps, and even as low as about 15 Kbps oreven 10 Kbps.

Wireless Audio Communications System

It is further contemplated that the streaming media communication systemof the invention has particularly useful applications within wirelessaudio communications networks, and in particular cellular telephonynetworks. Therefore, FIGS. 7 and 8 schematically show, with respectivelyincreasing amounts of detail, streaming media communications systems 700and 800 respectively specifically applied to wireless audiocommunications systems according to certain specific, respectiveembodiments of the present invention. While particular devices, systemparameters, or arrangements of communicating devices shown are believedto be beneficial in the overall application of the invention, they arenot to be considered limiting and may be suitably replaced with othersubstitutes according to one of ordinary skill based upon thisdisclosure. The various wireless communications systems 700 and 800,standards, and protocols referenced elsewhere in this disclosure arethus incorporated into this section for the purpose of integration withthe various aspects of compression, delivery, decompression, andtranscoding according to one embodiment of the invention.

Combination of the communications system 400 of one embodiment of thepresent invention with the other components of a cellular communicationsnetwork allows for the enhanced compression, delivery, and decompressionaccording to the invention to manifest in an increased quality ofservice for wireless audio communications. Improvements in cellularcommunications according to the invention include, without limitation,the following examples: increasing available bandwidth, extending rangeof reception, and providing graceful degradation while maintainingconnectivity during periods of low signal quality or reception levels.

More specifically, cellular telephony signals are characterized byrelatively high degrees of variability, due for example to the roamingpositions of clients, and limited cell ranges, atmospheric conditions,and significantly limited and changing available bandwidths over dailyuse cycles. Therefore, a self-optimizing CODEC management systemaccording to the present invention is particularly well suited to adjustthe appropriate communications and compression modalities to thechanging environment. At the very least, the increase in compressionefficiency and resulting decrease in bandwidth used for given signals isa valuable achievement as wireless channel traffic continues to congest.

In one particular regard, the increased compression efficiency accordingto the present invention is well applied to improving bandwidth issuesduring “soft hand-offs” between cells, as illustrated in FIG. 9. Duringcellular phone communications, whenever a transmitter or receivermigrates between cell coverage zones, communications bandwidthrequirements and resultant costs are increased by systemic requirementto “pass off” active communications between cells. The act of passingoff the communication results in a “backhaul” channel from thepreviously active cellular transmitter to a central office forforwarding to a newly active cellular transmitter. The backhaul channelrepresents a significant use of bandwidth. Savings will result fromincreased compression. As Figure shows, such “backhauling” may include adoubling (media sent back from first cell being left and resent tosecond cell for transmission) or even a quadrupling (overlappingcommunication from both first and second cells) in the bandwidth usedfor communicating a particular signal.

The media communications system 400 of the present invention mayrecognize when backhaul is occurring, such as according to thetransmission channel diagnostics provided in the software agent(s), andmay respond by adjusting the degree of compression to compensate.

WAP Video Gateway

With a particular view of the rapid growth observed and predicted in thewireless or mobile Internet, embodiments of the present inventioncontemplate application of the intelligentcompression/delivery/decompression embodiments in combination with WAPGateway functionality.

A system and method is therefore also provided according to theinvention for encoding, compressing and transmitting complex digitalmedia (e.g., video pictures) via bandwidth-constrained wirelesscommunications systems utilizing Wireless Applications Protocol (WAP).In one embodiment, data is processed by the system, resident at a servernode(s), employing neural networks with artificial intelligence. Samplesegments of data are captured from the input stream and processed tocomply with requirements unique to the class of clients. As is describedin detail above, the system correlates the continuously varying digitaldata streams' characteristics with libraries of pre-developedexperientially learned rules and with externally imposed constraints tooptimally choreograph the coherence, continuity and detail of the dataas ultimately received, decoded and presented at the client interface.

A gateway provided with the added functionality of the streaming mediacommunications system herein described is shown schematically in FIG. 8.According to the WAP gateway system 830, a client agent is provided thatis adapted to run on a variety of platforms, and requires no specializedhardware to decode the video streams. According to use of the streamingmedia delivery system of the invention elsewhere herein described, theviewer of the WAP device maintains constant communication with thesystem server upstream, such that the user-side client 825 may providethe encoding platform with relevant information for streaming mediacommunication, including without limitation: available screen size,processing power, client operating system and browser version,connection speed and latency, thereby allowing the streaming mediadelivery system to tailor the stream to each individual client it“talks” to. Accordingly, an AI driven server 830 incorporating the AIcompression as herein described may be combined with a WAP Gateway 830,combining the necessary WAP to TCP/IP protocol (or other protocol, e.g.dual server stack) translation with a Video and Audio Server 835employing compression, delivery, and decompression systems and methodsherein described. The WAP Gateway 830 may further include a videotranscoder, such as for example incorporating the transcoder systems andmethods herein described. An appropriate host architecture according tothis system (not shown) generally includes a rack mount system runningLinux OS with a modified WAP Gateway 830 or as a software plug-in toexisting servers.

This WAP gateway system 830 may be further provided in a Master/Slaverelationship as another beneficial aspect of the overall streaming mediadelivery architecture (applicable to other delivery systems other thanspecifically wireless). Various content distribution networks, such asavailable through Akamai and Inktomi, have capitalized on the concept ofimproving data delivery over the Internet by using “smart caching” onservers which reside on the borders of the Internet. Such a Master/Slaverelationship is maintained by the present system wherein a Master Serverresides at the source of the content to be delivered and Slave Serversreside on the borders. These servers communicate “intelligently” tooptimize the content delivery over the Internet and reduce latency,bandwidth and storage requirements, improving the overall quality of thevideo/audio stream to the end-user and decreasing the cost of mediadelivery to the content provider.

The WAP gateway 830 of the present invention supports continued growthin mobile communications, as large telecommunications operators aretransitioning to multi-service broadband networks, and as the number ofsubscribers to the mobile Internet continues to expand rapidly. Inparticular, mobile communications is a broad class of systems andprotocols, each having its own constraints and needs for interactingdevices to communicate streaming media. The Gateway 830 in aparticularly beneficial aspect may support a variety of “2G” systemswith upgradability for upcoming “2.5G” and “3G” network technologies(numerical progression of systems generally represents progression ofInternet-enabled capabilities).

The following Table 3 provides examples of known mobile communicationstandards, and provides certain related information used by the AIsystem of the present invention for optimizing communication ofstreaming media amongst the field of mobile destination devices as mediaplayers:

TABLE 3 Existing/Soon Anticipated Mobile Communications Standards MODEBAUD RATE (generally) GSM (2G) 9.6 Kbps CDMA 9.6 Kbps TDMA 14.4 KbpsCDPD 14.4 Kbps iMODE 128 Kbps GPRS 144 Kbps WCDMA or CDMA2000 144 Kbpsto 2 Mbps GSM (3G) 2 Mbps

In addition, the present invention is particularly beneficial in itsability to stream a wide variety of media signals to various differenttypes of wireless communications devices. Examples of wirelesscommunications devices that are appropriate for use with the streamingmedia communications systems and methods of the invention, and which thesystems and methods support interchangeably, are provided in thefollowing Table 4:

TABLE 4 Examples of Internet-enabled PDA's SCREEN SCREEN MODEM CONNECTDEVICE MAKE SPEED MEMORY DEPTH SIZE TYPE SPEED iPAQ Compaq 206 MHz 16-64Mb 12 b/pixel 320 × 240 External 9600-14.4 Kbps color (e.g. CDPD) PalmVII Palm  33 MHz  4-16 Mb 4 b/pixel Internal 14.4 Kbps b/w 8 b/pixelcolor Handspring Palm  33 MHz  4-16 Mb 4 b/pixel External 14.4 Kbps b/w;8 b/pixel color Blackberry Research-  33 MHz 4 Mb 2 b/pixel Internal9.6-14.4 Kbps In-Motion b/w Jornada HP 133 MHz 16-32 Mb 18 b/pixel 320 ×240 External 9.6-14.4 Kbps Casseopeia Casio 150 Mhz 16-31 Mb 12 b/pixel320 × 240 External 9.6-14.4 Kbps

Various specific examples are described later below that provideobservations of actual wireless Internet applications of the inventionas herein described. Such examples include use of a CODEC libraryaccording to varied parameters associated with at least the following(without limitation): destination wireless communication device;transmission channel; communications protocol; and the respectivestreaming media signals themselves. The various particular features ofthe systems and methods used according to these examples arecontemplated as further defining independently beneficial aspects of theinvention.

Shared Interactive Environment

A system and method is also provided according to the invention forenabling real-time remote client interaction with a high-definition,multi-dimensional, multi-participant simulated environment without theneed for significant client-side processing capacity. More specifically,FIG. 10 shows an overall streaming media communication system as appliedto shared interactive gaming according to the invention.

This system includes: (i) a proxy server; (ii) graphics renderingcapabilities; (iii) a client software agent for feedback of clientinputs to the game; (iv) a client software agent for supporting thedelivery system of the invention; and (v) streaming from the server tothe client. It is contemplated that for multiple clients, whichtypically represent shared interactive gaming by design, multiplecomponents as just described are provided to support each client.

The interactive gaming embodiments contemplate implementation of datacompression and delivery embodiments with devices that are alsodestination devices for compressed signals from other like, remotelylocated device systems. This arrangement is broadly beneficial, such asfor example in further interactive media implementations such as videoconferencing and the like. Accordingly, each remote system is both asource and a destination device, and sends and receives agents betweenit and other remote systems.

Destination Device

Although the communications systems of the present invention enablescommunication of streaming media signals to a wide variety ofdestination devices, a further contemplated feature of the inventionprovides a remote receiver to be housed as a destination device/playerby client users. This set-top player may be adapted to serve at leastone, though preferably multiple ones, and perhaps all, of the following:Video on Demand (VOD); Music on Demand (MOD); Interactive Gaming onDemand (IGOD); Voice Over Internet Protocol (“VoIP”), any technologyproviding voice telephony services over IP connections; Television WebAccess; Digital Video Recording to record, pause, and playback livetelevision; e-mail; chat; a DVD player; and other applications apparentto one of ordinary skill. All of this may be delivered to existingtelevisions in the comfort of users' own homes. Moreover, clientsutilizing this box, or other systems interfacing with the communicationssystem of the invention, may receive DVD quality video and surroundsound over cable and DSL connections.

EXAMPLES

For the purpose of further illustrating the highly beneficial resultsthat may be achieved according to the invention, the following areexamples of specific embodiments that have been used for different typesof streaming media communication, including observed results withpertinent discussion. These examples illustrate communication the samepre-recorded video over different transmission channels and to differentdestination devices, wherein the pre-recorded video has the followingoriginating properties: 720 lines of resolution and 32 bits of colorinformation, an originating file size of about 1.4 Gigabytes.

Example 1

An “iPAQ” model 3650 hand-held PDA (commercially available from Compaq,Inc. for approximately $500 at the time of this disclosure) wasprovided. The PDA was interfaced with a 14.4 Kbps (max) wireless CDPDmodem (“AirCard 300” wireless external modem, commercially availablefrom Sierra Wireless for approximately $200 at the time of thisdisclosure) using an extension assembly (iPAQ™ PCMCIA expansion sleevefrom Compaq, Inc.) with a PCMCIA card slot that couples to the wirelessmodem. The iPAQ™ used is generally characterized as having the followingprocessing parameters: 206 MHz processor; 32 Mb memory; 12 b/pixelcolor; 240×320 screen dimensions; PocketPC™ operating system version 3.0from Microsoft Corp. and stereo sound. The iPAQ™ was connected to theInternet in San Francisco, Calif. via the interfaced CDPD modem over theAT&T cellular wireless carrier system at a connection bandwidth of about13.3 Kbit/sec. A server located in San Jose, Calif. (approximately 50 miaway) was contacted by the PDA employing the http and rtsp protocols,and the PDA was used to initiate a request for a pre-recorded videohaving the following originating properties: 720 lines of resolution and32 bits of color information, the originating file size was 1.4Gigabytes. Within about seven seconds, a compressed approximation of thepre-recorded video was received, decompressed, and displayed by the PDAon the PDA's screen. The entire video was seen at 240×320×12 bppresolution in full motion without observable delays or defects.

Example 2

A “Jornada™” model 548 hand-held PDA (commercially available from HP,Inc. for approximately $300 at the time of this disclosure) wasprovided. The PDA was interfaced with a 9.6 Kbps (max) wireless CDMAphone (“Motorola i85s” wireless external digital cellular phone,commercially available from Motorola authorized vendors forapproximately $200 at the time of this writing) using adaptor cables(Motorola and HP RS-232 standard interface cables from Motorola and HP.)that couple the phone and PDA together to form a wireless modem. TheJornada model PDA device used is generally characterized as having thefollowing processing parameters: 133 MHz processor; 32 Mb memory; 12b/pixel color; 240×320 screen dimensions; PocketPC™ operating systemversion 3.0 from Microsoft Corp. and stereo sound. The Jornada™ wasconnected to the Internet in Newark, N.J. via the interfaced CDMAphone/modem over the Nextel digital cellular wireless carrier system ata connection bandwidth of 8 Kbit/sec. A server located in San Jose,Calif. (approximately 2900 mi away) was contacted by the PDA employingthe http and WDP protocols, and the PDA was used to initiate a requestfor a pre-recorded video having the following originating properties:720 lines of resolution and 32 bits of color information, theoriginating file size was 1.4 Gigabytes. Within about seven seconds, acompressed approximation of the pre-recorded video was received,decompressed, and displayed by the PDA on the PDA's screen. The entirevideo was seen at 176×120×8 bpp in full motion without observable delaysor defects.

Example 3

A “Set-top Box” model st850 book PC (commercially available from MSI,Inc. for approximately $300 at the time of this writing) was provided.The Set-top Box was interfaced with a 10 Mbps (max) ethemet/802.11connection using CAT5 ethernet cables (Generic) that couple the Set-topBox to a broadband connection (DS3). The Set-top Box used is generallycharacterized as having the following processing parameters: 400 MHzprocessor; 64 Mb memory; 32 b/pixel color; 720 lines of screenresolution; Windows CE operating system version 2.11 from MicrosoftCorp. and AC3 digital 6 channel surround-sound. The Set-top Box wasconnected to the Internet in Newark, N.J. via the interfaced shared DS3connection over the Alter.Net Internet Backbone at a connectionbandwidth of 376 Kbit/sec. A server located in San Jose, Calif.(approximately 2900 mi away) was contacted by the Set-top Box employingthe http and rtsp protocols, and the Set-top Box was used to initiate arequest for a pre-recorded video having the following originatingproperties: 720 lines of resolution and 32 bits of color information,the originating file size was 1.4 Gigabytes. Within About nine seconds,a compressed approximation of the pre-recorded video was received,decompressed, and displayed by the Set-top Box on a commerciallyavailable reference monitor's (Sony) screen. The entire video was seenat 720 lines×32 bpp in full motion without observable delays or defects.

While various particular embodiments have been herein shown anddescribed in great detail for the purpose of describing the invention,it is to be appreciated that further modifications and improvements maybe made by one of ordinary skill based upon this disclosure withoutdeparting from the intended scope of the invention. For example, variouspossible combinations of the various embodiments that have not beenspecifically described may be made and still fall within the intendedscope of the invention. According to another example, obviousimprovements or modifications may also be made to the variousembodiments and still fall within the intended scope of this invention.

1. A method comprising: obtaining a media signal to be communicated to adestination agent, the media signal being separated into a plurality ofsegments each comprising a number of temporally adjacent frames; andrepeating for each of the plurality of segments: testing a plurality ofdifferent CODECs on the segment to determine how each CODEC encodes thesegment in terms of quality and compression level; automaticallyselecting the CODEC that produces the highest quality encoded output forthe segment according to a set of criteria without exceeding a bandwidthconstraint; delivering the segment encoded using the selected CODEC tothe destination agent; and reporting to the destination agent whichCODEC was used to encode the segment; wherein at least two segments areencoded using different CODECs.
 2. The method of claim 1, furthercomprising storing an association between one or more identifiedcharacteristics of a segment and the selected CODEC.
 3. The method ofclaim 2, further comprising: in response to a subsequent segment of themedia signal being found to have the same one or more identifiedcharacteristics, automatically selecting the CODEC from the storedassociation to encode the subsequent segment.
 4. The method of claim 3,wherein the CODEC is automatically selected from the stored associationby an artificial intelligence (AI) system.
 5. The method of claim 4,wherein the AI system comprises a neural network.
 6. The method of claim2, wherein the characteristics of the segment are selected from thegroup consisting of temporal characteristics, spatial characteristics,and logical characteristics.
 7. The method of claim 1, wherein testingfurther comprises: storing a baseline snapshot of the segment; and foreach CODEC to be tested: encoding the segment at or below the bandwidthconstraint using one of the CODECs; decoding the segment using the sameCODEC; and comparing the quality of the decoded segment with thebaseline snapshot according to the set of criteria.
 8. The method ofclaim 7, wherein comparing further comprises comparing the qualityaccording to a Peak Signal-to-Noise Ratio (PSNR).
 9. The method of claim1, further comprising adjusting the bandwidth constraint based onconstraints of at least one of the destination agent and a transmissionchannel to the destination agent.
 10. The method of claim 1, wherein theCODECs are selected from the group consisting of block CODECs, fractalCODECs, and wavelet CODECs.
 11. The method of claim 1, whereindelivering further comprises transmitting the encoded segment to thedestination agent through a network; and wherein reporting comprisessending an indication of which CODEC was used to encode the segmentthrough the network to the destination agent.
 12. The method of claim 1,wherein delivering further comprises storing the encoded scene on astorage medium; and wherein reporting comprises storing an indication ofwhich CODEC was used to encode the scene on the storage medium.
 13. Asystem comprising: an input module to obtain a media signal to becommunicated to a destination agent, the media signal being separatedinto a plurality of segments each comprising a number of temporallyadjacent frames; a selection module to test a plurality of differentCODECs on each of the plurality of segments to determine how each CODECencodes each segment in terms of quality and compression level, whereinthe selection module is further to select the CODEC that produces thehighest quality encoded output for each segment according to a set ofcriteria without exceeding a bandwidth constraint; an output module todeliver each segment encoded using a respective selected CODEC to thedestination agent and report to the destination agent which CODEC wasused to encode each segment.
 14. The system of claim 13, wherein theselection module tests the plurality of CODECs on a segment by storing abaseline snapshot of the segment and, for each CODEC to be tested,encoding the segment at or below the bandwidth constraint using one ofthe CODECs, decoding the segment using the same CODEC, and comparing thequality of the decoded segment with the baseline snapshot according tothe set of criteria.
 15. The system of claim 14, wherein the quality iscompared according to a Peak Signal-to-Noise Ratio (PSNR).
 16. Thesystem of claim 13, wherein the selection module is to store anassociation between one or more identified characteristics of a segmentand the selected CODEC.
 17. The system of claim 16, wherein theselection module, in response to a subsequent segment of the mediasignal being found to have the same one or more identifiedcharacteristics, is to automatically select the CODEC from the storedassociation to encode the subsequent segment.
 18. The system of claim17, wherein the CODEC is automatically selected from the storedassociation by an artificial intelligence (AI) system.
 19. The system ofclaim 18, wherein the AI system comprises a neural network.
 20. Thesystem of claim 16, wherein the characteristics of the scene areselected from the group consisting of temporal characteristics, spatialcharacteristics, and logical characteristics.
 21. The system of claim13, wherein the selection module is to adjust the bandwidth constraintin response to constraints of at least one of the destination agent anda transmission channel to the destination agent.
 22. The system of claim13, wherein the CODECs are selected from the group consisting of blockCODECs, fractal CODECs, and wavelet CODECs.
 23. A system comprising:means for obtaining a media signal to be communicated to a destinationagent, the media signal being separated into a plurality of segmentseach comprising a number of temporally adjacent frames; means fortesting a plurality of different CODECs on each of the plurality ofsegments to determine how each CODEC encodes the segment in terms ofquality and compression level; means for selecting the CODEC thatproduces the highest quality encoded output for each segment accordingto a set of criteria without exceeding a bandwidth constraint; means fordelivering each segment encoded using a respective selected CODEC to thedestination agent and report to the destination agent which CODEC wasused to encode each segment.
 24. The system of claim 23, wherein thetesting means tests the plurality of CODECs on a segment by storing abaseline snapshot of the segment and, for each CODEC to be tested,encoding the segment at or below the bandwidth constraint using one ofthe CODECs, decoding the segment using the same CODEC, and comparing thequality of the decoded segment with the baseline snapshot according tothe set of criteria.
 25. The system of claim 24, wherein the quality iscompared according to a Peak Signal-to-Noise Ratio (PSNR).
 26. Thesystem of claim 23, wherein the selection means stores an associationbetween one or more identified characteristics of the segment on whichthe CODECs were tested and the selected CODEC.
 27. The system claim 26,wherein the selection means, in response to a subsequent segment of themedia signal being found to have the same one or more identifiedcharacteristics, automatically selects the CODEC from the storedassociation to encode the subsequent segment.
 28. The system of claim27, wherein the selection means comprises an artificial intelligence(AI) system.
 29. The system of claim 28, wherein the AI system comprisesa neural network.
 30. The system of claim 26, wherein thecharacteristics of the scene are selected from the group consisting oftemporal characteristics, spatial characteristics, and logicalcharacteristics.
 31. The system of claim 23, wherein the selection meansis to adjust the bandwidth constraint in response to constraints of atleast one of the destination agent and a transmission channel to thedestination agent.
 32. The system of claim 23, wherein the CODECs areselected from the group consisting of block CODECs, fractal CODECs, andwavelet CODECs.
 33. A method comprising: obtaining a media signal to becommunicated to a destination agent, the media signal being separatedinto a plurality of segments each comprising a number of temporallyadjacent frames; and repeating for each of the plurality of segments:simultaneously testing a plurality of different CODECs on the segment todetermine how each CODEC encodes the segment in terms of quality andcompression level; automatically selecting the CODEC that produces thehighest quality encoded output for the segment according to a set ofcriteria without exceeding a bandwidth constraint; delivering thesegment encoded using the selected CODEC to the destination agent; andreporting to the destination agent which CODEC was used to encode thesegment.
 34. The method of claim 33, wherein the CODECs aresimultaneously tested on the segment using a plurality of processorsoperating in parallel.
 35. The method of claim 33, wherein testingfurther comprises: storing a baseline snapshot of the segment; and foreach CODEC to be tested: encoding the segment at or below the bandwidthconstraint using one of the CODECs; decoding the segment using the sameCODEC; and comparing the quality of the decoded segment with thebaseline snapshot according to the set of criteria.